• 대한전자공학회논문지SP
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• 제48권5호
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• pp.115-122
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• 2011

조향벡터(steering vector)에 에러가 있으면 적응 어레이(adaptive array)는 심한 성능저하를 겪게 된다. 이러한 에러로 인한 성능저하를 개선하기위해 DCRCB(doubly constrained robust Capon beamformer)에서는 벡터 norm 제한아래 구체 불확실 집합(spherical uncertainty set) 내의 벡터 중 출력전력을 최대로 하는 벡터를 조향벡터(steering vector)로 사용한다. 좋은 성능 개선을 위해서 불확실 집합의 반경, 즉 불확실 한계를 적절히 설정해야 하는 문제가 있다. 본 논문에서는 이를 해결하기 위해 반복탐색을 통해 조향벡터를 구하는 방식을 제안한다. 기존의 알려진 반복탐색 방식에서는 반복 종료를 위해 어떤 기준값을 결정해야 하는데, 이에 따른 어려움이 있다. 제안방식에서는 추정된 벡터와 신호부공간 거리가 더 이상 작아 지지 않으면 반복을 종료하며, 값 설정과 관련된 어떤 어려움도 없다. 시뮬레이션 결과에 따르면, 제안방식은 기존반복방식 그리고 최적의 불확실 한계로 설정된 표준 DCRCB 보다도 우수한 성능을 보여준다.

• 한국항공우주학회지
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• 제35권11호
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• pp.983-989
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• 2007

위그선(WIG: Wing In Ground effect)은 해수면상의 저고도에서 운영되기 때문에 조류충돌에 쉽게 노출될 수 있으며 특히 리딩에지(Leading Edge)는 충돌가능성이 높기 때문에 조류충돌에 대한 구조적 안정성 검증과정이 반드시 필요하다. 이러한 항공기에 대한 조류충돌은 매우 복잡한 현상중의 하나로 다양하고 불확실한 파라메터들이 존재한다. 조류충돌에 대한 해석과정에 있어서 불확실성이 존재하는 파라메터들이 충돌 해석결과에 미치는 영향력을 분석하기 위해 퍼지이론을 적용한 유한요소 해석을 수행하였다. 불확실한 파라메터들이 갖는 조류충돌에 대한 영향력은 비선형 충돌해석 프로그램인 LS-DYNA 3D를 사용하여 해석하였으며 조류충돌 현상에 존재하는 다양하고 불확실한 파라메터들은 퍼지숫자(Fuzzy number)와 멤버십 함수(Membership function)로 표현하여 퍼지연산 및 변환기법(Transformation method)을 통해 해석과정에 적용하였다. 결론적으로 불확실성이 존재하는 파라메터들이 조류충돌 현상에 미치는 영향력을 퍼지 연산을 통해 수치적으로 평가하였다.

• Structural Engineering and Mechanics
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• 제56권5호
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• pp.707-726
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• 2015

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

• Nuclear Engineering and Technology
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• 제48권3호
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Nuclear Engineering and Technology
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• 제45권6호
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• pp.767-790
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• 2013

MAAP4 is a computer code that can simulate the response of a light water reactor power plant during severe accident sequences, including actions taken as part of accident management. The code quantitatively predicts the evolution of a severe accident starting from full power conditions given a set of system faults and initiating events through events such as core melt, reactor vessel failure, and containment failure. Furthermore, models are included in the code to represent the actions that could mitigate the accident by in-vessel cooling, external cooling of the reactor pressure vessel, or cooling the debris in containment. A key element tied to using a code like MAAP4 is an uncertainty analysis. The purpose of this paper is to present a MAAP4 based analysis to examine the sensitivity of a key parameter, in this case hydrogen production, to a set of model parameters that are related to a Level 2 PRA analysis. The Level 2 analysis examines those sequences that result in core melting and subsequent reactor pressure vessel failure and its impact on the containment. This paper identifies individual contributors and MAAP4 model parameters that statistically influence hydrogen production. Hydrogen generation was chosen because of its direct relationship to oxidation. With greater oxidation, more heat is added to the core region and relocation (core slump) should occur faster. This, in theory, would lead to shorter failure times and subsequent "hotter" debris pool on the containment floor.

• 전자공학회논문지SC
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• 제45권5호
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• pp.1-7
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• 2008

본 논문에서는 변수 불확실성을 가지는 이산시간 특이시스템과 곱셈형 섭동의 약성(fragility)을 가지는 제어기에 대한 강인 안정화 기법과 강인 비약성(non-fragile) 제어기 설계방법을 제시한다. 강인 안정화를 만족하는 비약성 제어기가 존재할 조건과 제어기 설계방법 및 제어기의 비약성 척도를 볼록최적화(convex optimization)가 가능한 선형행렬부등식 접근방법을 이용하여 제안한다. 최대의 비약성 척도를 얻기 위하여 구한 제어기 충분조건은 모든 변수의 견지에서 선형행렬부등식으로 변형한다. 따라서, 제안한 강인 비약성 이산 제어기는 특이시스템의 변수 불확실성과 제어기의 약성에도 불구하고 안정성을 보장한다 마지막으로, 수치예제를 통하여 제안한 알고리듬의 타당성을 확인한다.

• 로봇학회논문지
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• 제11권4호
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• pp.248-255
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• 2016

Machining error makes the uncertainty of dimensional accuracy of the kinematic structure of a parallel robot system, which makes the uncertainty of kinematic accuracy of the end-effector of the parallel robot system. In this paper, the tendency of trajectory tracking error caused by the tolerance of design parameters of the parallel robot is analyzed. For this purpose, all the position errors are analyzed as the manipulator is moved on the target trajectory. X, Y, Z components of the trajectory errors are analyzed respectively, as well as resultant errors, which give the designer of the manipulator the intuitive and deep understanding on the effects of each design parameter to the trajectory tracking errors caused by the uncertainty of dimensional accuracy. The research results shows which design parameters are critically sensitive to the trajectory tracking error and the tendency of the trajectory tracking error caused by them.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.324-328
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• 2005

This study is to figure out uncertainty relationship between input data and calibrated parameter on unsteady hydraulic routing model. The uncertainty would be present to model results as a variant water surface profile along the channel. Firstly, Manning's n is calibrated through the model with assumed uncertainty on input hydrograph. Then, spatially distributed n-values sets based on the calibrated n values are used to get water profile of each n-values set. The results show that ${\pm}0.002$ of error in Manning's n cause ${\pm}30cm$ of maximum water surface differences at the Sumjin river.

• Earthquakes and Structures
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• 제6권1호
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• pp.19-43
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• 2014

A risk assessment framework for evaluating building structures is implemented in this study. This framework allows considering sources of uncertainty both on structural capacity and seismic demand. In particular randomness on seismic load, incident angle, material properties, floor mass and structural damping are considered; in addition the choice of fibre modelling versus plastic hinge model is also considered as a source of uncertainty. The main objective of this work is to study the contribution of these sources of uncertainty on the fragilities of steel and steel-reinforced concrete composite 3D building structures. The fragility curves are expressed in the form of a two-parameter lognormal distribution where vertical statistics in conjunction with metaheuristic optimization are implemented for calculating the two parameters.