• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2084-2093
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• 2022

Probabilistic safety assessment is widely used to quantify the risks of nuclear power plants and their uncertainties. When the lognormal distribution describes the uncertainties of basic events, the uncertainty of the top event in a fault tree is approximated with the sum of lognormal random variables after minimal cutsets are obtained, and rare-event approximation is applied. As handling complicated analytic expressions for the sum of lognormal random variables is challenging, several approximation methods, especially Monte Carlo simulation, are widely used in practice for uncertainty analysis. In this study, a theoretical approach for analyzing the sum of lognormal random variables using an efficient numerical integration method is proposed for uncertainty analysis in probability safety assessments. The change of variables from correlated random variables with a complicated region of integration to independent random variables with a unit hypercube region of integration is applied to obtain an efficient numerical integration. The theoretical advantages of the proposed method over other approximation methods are shown through a benchmark problem. The proposed method provides an accurate and efficient approach to calculate the uncertainty of the top event in probabilistic safety assessment when the uncertainties of basic events are described with lognormal random variables.

• Nuclear Engineering and Technology
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• 제37권2호
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• pp.139-150
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• 2005

A robust control design procedure for a nuclear reactor has been developed and experimentally validated on the Penn State TRIGA research reactor. The utilization of the robust controller as a component of an autonomous control system is also demonstrated. Two methods of specifying a low order (fourth-order) nominal-plant model for a robust control design were evaluated: 1) by approximation based on the 'physics' of the process and 2) by an optimal Hankel approximation of a higher order plant model. The uncertainty between the nominal plant models and the higher order plant model is supplied as a specification to the ,u-synthesis robust control design procedure. Two methods of quantifying uncertainty were evaluated: 1) a combination of additive and multiplicative uncertainty and 2) multiplicative uncertainty alone. The conclusions are that the optimal Hankel approximation and a combination of additive and multiplicative uncertainty are the best approach to design robust control for this application. The results from nonlinear simulation testing and the physical experiments are consistent and thus help to confirm the correctness of the robust control design procedures and conclusions.

• 한국추진공학회지
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• 제24권3호
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• pp.18-30
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• 2020

본 연구는 고체추진기관의 추력측정불확도 추정 방법에 관한 것이다. 힘 측정불확도 추정 지침은 ISO와 국내외 기구에서 제공하고 있으나 모든 내용이 실험실에서 운용하는 하중시험기와 하중 센서의 교정을 중심으로 기술되고, 개념적으로 기술되어 있다. 추력시험대 불확도의 주요 원인인 교정식과 선형화 불확도의 추정에 대해서는 해당 지침을 직접 적용할 수는 없다. 본 논문에서는 측정불확도 기본 개념을 이용하여 교정식 불확도와 교정식의 선형화 불확도를 추정하는 식을 만들고, 이를 추력 시험대의 추력측정불확도에 추정하여 적용하였으며, 비교적 간단한 추력측정불확도 추정 방법을 제안하였다.

• 한국정밀공학회지
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• 제25권12호
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of the Korean Physical Society
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• 제73권9호
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• pp.1247-1254
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• 2018

We study the uncertainty stemming from different theoretical models in the spectroscopic factors extracted from experiments. We use three theoretical approaches, the distorted wave Born approximation (DWBA), the adiabatic distorted wave approximation (ADWA) and the continuum discretized coupled-channels method (CDCC), and analyze the $^{12}C(d,p)^{13}C$, $^{14}C(d,p)^{15}C$ reactions. We find that the uncertainty associated with the adopted theoretical models is less than 20%. We also investigate the contribution from the remnant term and observe that it gives less than 10% uncertainty. We finally make an attempt to explain the discrepancy in the spectroscopic factors of $^{17}C(\frac{3}{2}^+)$ between the ones extracted from experiments and from shell model calculations by analyzing the $^{16}C(d,p)^{17}C$ reaction.

• 한국산업정보학회논문지
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• 제28권1호
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• pp.27-34
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• 2023

최상의 에이전트-작업 할당을 결정하는 문제는 조합 최적화(combinatorial optimization)의 대표적인 문제이자 NP-난해(NP-hard)임이 알려져 있다. 본 연구에서는 에이전트와 작업의 할당 시 결정되는 작업 수행 확률(completion probability)이 불확실한 상황에서의 문제를 다룬다. 에이전트나 작업 내부의 요인 혹은 시스템 외적인 요소로 인한 작업 수행 확률은 고정적이기보다 불확실성을 갖는 것이 일반적이다. 불확실성을 고려하지 않은 할당 결정은 변동성이 있는 현실 상황에서 효과적이지 않은 결정이 될 수 있다. 작업 수행 확률의 불확실성을 수학적으로 반영하기 위해 본 연 구에서는 추계적 계획법(stochastic programming)을 활용한 수리 모형을 제시한다. 본 연구에서는 효율적으로 문제를 풀기 위해 표본 평균 근사법(sample average approximation)을 활용한 알고리즘을 제안한다. 본 문제 해결 방법론을 이용해 효과적인 할당 결정과 상한값과 하한값을 구할 수 있고, 결과의 성능을 확인하기 위해 최적 격차(optimality gap)와 분산을 실험을 통해 제시한다. 이를 통해 알고리즘으로 구한 할당 결정의 우수성 및 강건성을 보인다.

• 한국군사과학기술학회지
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• 제13권4호
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• pp.665-672
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• 2010

This paper describes Monte Carlo Simulation(MCS) to assess the uncertainty of dynamic pressure calibrator and the expanded uncertainty results that were compared by GUM approximation and MCS. MCS uncertainties were computed using defining a domain of possible inputs, generating inputs randomly using probability distribution, performing a deterministic computation repeatedly and aggregating the results. It was revealed that the expanded uncertainty between GUM and MCS was different from each other. the expanded uncertainties were 0.5366%, 0.4856%, respectively. MCS is a suitable method for determining the uncertainty of simple and complex measurement systems. It should be more widely used and studied in measurement uncertainty calculations.

• Journal of Ship and Ocean Technology
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• 제9권1호
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• pp.64-71
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• 2005

In probabilistic design, the challenge is to estimate the uncertainty propagation, since outputs of subsystems at lower levels could constitute inputs of other systems or at higher levels of the multilevel systems. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and Taguchi-based integration. When applied to reliability-based design optimization (RBDO) under uncertainty, it is investigated which type of applications each method is best suitable for. Two nonlinear analytical examples and one vehicle crashworthiness for side-impact simulation example are employed to investigate the unique features of the presented techniques for uncertainty propagation. This study aims at helping potential users to identify appropriate techniques for their applications in the multilevel design.

• 한국공작기계학회논문집
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• 제18권1호
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.59-62
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• 1991

This paper describes an effective algorithm for evaluating the reliability indices and calculating the production cost for generation system with thermal, hydro and pumped storage plants. Using the Energy Invariance property, this algorithm doesn't need deconvolution process which gives large burden in computing time. In order to consider an adaptable load model, we consider the system load with forecasting uncertainty. The proposed algorithm is applied to the KEPCO system and its result shows high accuracy and less computing time.