• Korean Chemical Engineering Research
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• 제50권3호
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• pp.471-478
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• 2012

이산화탄소 포집 및 저장(CCS) 기반시설은 온실가스 배출량의 획기적인 감축과 관련하여 중요한 역할을 하고 있다. CCS 기반시설에 있어서의 구체적인 과제는 넓은 지역에 다양하게 분포되어 있는 대규모 방출원으로부터 $CO_2$를 포집한 뒤 수송하여 적절한 저장사이트에 주입하는 일련의 과정을 상업적 규모로 실증하는 것이다. CCS 기반시설의 상업적 도입을 위해 기술 경제적 타당성을 분석하는 많은 연구들이 수행되어 왔다. 하지만, 하나의 일관된 분석을 하기 위해 $CO_2$ 배출량, $CO_2$ 감축 비용, 탄소세 등과 같은 다양한 데이터의 불확실성들이 존재한다. CCS 기반시설을 설계 및 운영하는데 있어 이러한 데이터의 불확실성들을 고려한 연구들은 거의 진행되어 오지 않았다. 본 논문에서는 CCS 기반시설을 설계 및 운영하는 데 있어 불확실한 데이터인 CCS 운영비용과 탄소세를 고려한 2 단계 확률론적 계획 모델을 개발 하였다. 제시된 모델은 데이터의 불확실한 환경에도 불구하고 $CO_2$ 감축목표를 만족시키기 위해 $CO_2$ 포집, 저장, 수송 등 CCS 기반시설의 최적 설계 및 운영 전략을 결정할 수 있게 하고, 요구되는 연간 $CO_2$ 총 비용을 예측 가능하게 한다. 또한, 본 연구에서 제안한 모델의 타당성을 평가하기 위해 우리나라의 실제 사례에 적용해 보았다. 이 사례 연구를 통해 얻은 결과는 다양한 불확실한 요소들이 존재하는 환경하에 CCS 기반시설을 설계 및 운영하는 데 있어 최적의 결정을 제시할 것이다.

• 한국재난정보학회 논문집
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• 제17권4호
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• pp.747-754
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• 2021

연구목적: 곡선 교량은 기하하적 특성으로 직선교량에 비해 복잡한 거동을 보이기 때문에 지진 안전성 평가가 반드시 이루어져야 한다. 본 연구에서는 곡선 거더를 갖는 교량의 강재 재료 특성의 불확실성을 고려한 지진 취약도 평가를 수행하였다. 연구방법: I형 곡선 거더를 갖는 교량의 유한요소 모델을 구축하였으며 선행연구에서 제시된 강재 특성의 통계적 매개변수를 이용하였다. 라틴 하이퍼큐브 기법을 이용하여 100개의 강재 재료 모델을 샘플링하였다. 경주지진의 지반가속도를 0.2g, 0.5g, 0.8g, 1.2g, 1.5g로 scale을 변화시켜 지진 취약도 평가를 수행하였다. 연구결과: 곡선거더의 지진 취약도 평가결과 한계상태가 190MPa일 때 0.03g 파괴가 시작되었으며 한계상태가 315MPa일 때 0.11g를 초과하면서 파괴가 시작되는 것으로 나타났다. 결론: 본 연구에서는 재료 불확실성을 고려한 지진 취약도 평가를 수행하였으며 추후 연구에서는 지진파의 불확실성과 재료의 불확실성을 동시에 고려한 지진 취약도 분석이 필요할 것으로 판단된다.

• 대한기계학회논문집
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• 제15권2호
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• pp.463-477
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• 1991

This study proposed a new method to design a robot manipulator control system capable of tracking the trajectories of joint angles in a reasonable accuracy to cover with actual situation of varying payload, uncertain parameters, and time delay. The direct adaptive model following control method has been used to improve existing industrial robot manipulator control system design. The proposed robot manipulator controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories predefined by the designer. The manipulator control system studied has two loops: they are an inner loop on adaptive model following controller to compensate nonlinearity in the manipulator dynamic equation and to decouple the coupling terms and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstability approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in various cases, load variation, parameter uncertainties. and time delay. Since the proposed adaptive control method requires only a small number of parameters to be estimated, the controller has a relatively simple structure compared to the other adaptive manipulator controllers. Therefore, the method used is expected to be well suited for a high performance robot controller under practical operation environments.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• Safety and Health at Work
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• 제11권3호
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• pp.322-334
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• 2020

Background: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O₂, N₂, and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.

• 대한안전경영과학회지
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• 제6권3호
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• pp.249-273
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• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Structural Engineering and Mechanics
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• 제62권4호
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• pp.507-517
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• 2017

Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권2호
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• pp.227-243
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• 2015

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

• 한국수자원학회논문집
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• 제35권4호
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• pp.385-395
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• 2002

하천에서의 수질변동을 예측하기 위해 FOEA(First-Order Error-Analysis)와 Monte Carlo 모의를 적용한 추계학적 모형을 개발하였다. 영향메트릭스(Influential matrix)를 이용한 민감도 분석을 실시하여 주요 반응계수를 결정하였고, BFGS(Broyden-Fletcher-Goldfarb-Shanno) 최적화 기법을 사용하여 주요 반응계수 값을 산정하였다. 본 모형을 확정론적 수질해석과 동일한 실제 하도구간에 적용하여 추계학적 수질해석을 실시하였고, 그 결과는 확정론적 해석결과와 잘 일치하였다. 유량과 수질, 반응계수 등에 포함된 불확실도가 하류단의 불확실도에 끼치는 영향을 산정하기 위해 상류단과 지류의 유량 및 수질에 대한 불확실도, 그리고 반응계수의 불확실도에 대한 분석과정이 모형에 포함되었다. 모의수행 결과로부터 각 변수들이 가지고 있는 불확실도가 총 불확실도에 끼치는 영향에 대한 기여도를 산정 할 수 있었다.

• 한국환경과학회지
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• 제15권2호
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.