• 한국가스학회지
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• 제7권4호
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• pp.44-52
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• 2003

본 논문은 원자력발전소 방화벽에 설치된 케이블관통부 충전시스템(CPFS: Cable penetration fire stop) 안에서 일어나는 동적 열전달 현상을 수식화하고, 새로운 혼합알고리즘을 이용해서 수치적으로 계산하여, 3차원 그래픽으로 나타내는 작업에 관한 연구이다. CPFS 내에서의 열전도 현상을 주어진 초기조건과 경계조건하에서 포물선 편미분방정식(Parabolic PDE)으로 수식화하였다. 계산을 단순화하기 위하여 전체 열 흐름을 z-축직선상에서의 일어나는 열전도 성분과 x-y-좌표 평면상에서 일어나는 열전도 성분으로 나누었다. z-축과 평행한 직선상에서 일어나는 열전도를 나타내는 PDE는 연속과완화법(SOR: Sequential over-relaxation)을 이용하여 유한불연속 점들에 대한 연립상미분방정식(ODE)으로 만들어서 풀었고, x-y-좌표 평면상에서 일어나는 열전도에 관한 PDE는 Galerkin 유한요소법(FEM: Finite element method)을 적용하여 ODE로 전환해서 풀었다. 여기서 시간과 공간의 함수인 온도는 각 직선상의 점들과 각 평면상의 요소절점들에 대해서 일정한 시간간격으로 초기온도와 경계온도를 업데이트하여 번갈아 가며 계산한다. 이러한 일련의 계산결과를 바탕으로 CPFS시스템 내에서의 온도분포의 동적인 변화를 계산해 낼 수 있었다. 결론적으로 관통하는 케이블이 CPFS시스템의 온도분포에 매우 중요한 역할을 한다는 것을 알 수 있었다. 시뮬레이션 결과는 CPFS내의 온도분포를 쉽게 이해할 수 있도록 3차원 그래픽으로 나타냈으며, 관통하는 케이블이 방화시스템의 온도분포에 매우 중요한 영향을 끼친다는 것을 알 수 있었다. 마지막으로 계산결과를 실험결과와 직접 비교함으로써, 개발된 모델과 계산 알고리즘의 정당성을 보였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제25회 추계학술대회논문집
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• pp.13-21
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• 2005

이 논문은 발열 반응에서 상이 변화하는 물질의 연속 방정식에서 유도되는 안정된 파면의 구조를 고려했다. 특별히 액체와 기체, 고체와 액체 사이의 동적인 파면 구조를 수치적으로 연구하였다. 1차원 충격파 구조 분석에 근거한 본 연구에 의하면 연소 시 나노 사이즈의 파면이 존재한다고 추정한다. 설명을 위해, 증발과 응축에는 n-heptane이 사용되었고, 용해와 응고에는 HMX를 사용하였다. 이 개념의 확장은 로켓 추진제와 같이 액체, 고체 연료의 넓은 범위 모두를 포함한다.

• 한국자동차공학회논문집
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• 제20권6호
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• pp.73-82
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• 2012

The main and side reactions of the three selective catalytic reduction (SCR) reactions with ammonia over a vanadium-based catalyst have been investigated using synthetic gas mixtures in the temperature range of $170{\sim}590^{\circ}C$. The three SCR reactions are standard SCR with pure NO, fast SCR with an equimolar mixture of NO and $NO_2$, and $NO_2$ SCR with pure $NO_2$. Vanadium based catalyst has no significant activity in NO oxidation to $NO_2$, while it has high activity for $NO_2$ decomposition at high temperatures. The selective catalytic oxidation of ammonia and the formation of nitrous oxide compete with the SCR reactions at the high temperatures. Water strongly inhibits the selective catalytic oxidation of ammonia and the formation of nitrous oxide, thus increasing the selectivity of the SCR reactions. However, the presence of water inhibits the SCR activity, most pronounced at low temperatures. In this study, the experimental results are analyzed by means of a dynamic one-dimensional isothermal heterogeneous plug-flow reactor (PFR) model according to the Eley-Rideal mechanism.

• Tribology and Lubricants
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• 제40권1호
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• pp.8-16
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• 2024

This study conducts numerical modeling and eigen-analysis of a rod-fastened rotor, which is mainly used in aircraft gas turbine engines in which multiple disks are in contact through curvic coupling. Nayak's theory is adopted to calculate surface parameters measured from the tooth profile of the curvic coupling gear. Surface parameters are important design parameters for predicting the stiffness between contact surfaces. Based on the calculated surface parameters, elastoplastic contact analysis is performed according to the interference between two surfaces based on the Greenwood-Williamson model. The equivalent bending stiffness is predicted based on the shape and elastoplastic contact stiffness of the curvic coupling. An equation of motion of the rod-fastened rotor, including the bending stiffness of the curvic coupling, is developed. Methods for applying the bending stiffness of a curvic coupling to the equation of motion and for modeling the equation of motion of a rotor that includes both inner and outer rotors are introduced. Rotordynamic analysis is performed through one-dimensional finite element analysis, and each element is modeled based on Timoshenko beam theory. Changes in bending stiffness and the resultant critical speed change in accordance with the rod fastening force are predicted, and the corresponding mode shapes are analyzed.

• 전기학회논문지
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• 제60권3호
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.