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진승완,김용은 한국물리학회 2017 새물리 Vol.67 No.8
The radioactivity of a chain-decaying source such as some radioactive isotopes contained in spent nuclear fuel (SNF) can be calculated either by solving the Bateman equation, by calculating the matrix exponential function, by using a Monte Carlo computation method, or by using a numerical integration method. When these methods are applied, the computation time exponentially increases as the number of generations of the damping chain increases. In this study, the radioactivity of SNF as a function time was obtained by using a spline interpolation method that is used to express vector images in computer graphics. We measured the computation time by increasing the number of data points and calculating the frequency of 'Not a Number error' in the calculation results obtained by using the five different methods. When the spline method was applied, the radioactivity of SNF as a function of time could be obtained in a shorter time compared to the other methods. 사용후핵연료(spent nuclear fuel, SNF)와 같이 사슬 붕괴하는 방사선원의 방사능은 베이트만 방정식을 풀이하거나 행렬지수함수를 이용하는 방법, 또는 몬테카를로 연산법이나 수치적분 등의 방법으로 계산해오고 있다. 이들 방법을 사용할 때 붕괴사슬의 세대수가 증가하면 증가할수록 계산에 걸리는 시간은 지수함수적으로 증가한다. 본 연구에서는 컴퓨터 그래픽 분야에서 벡터 이미지를 표현할 때 사용되는 스플라인 보간법과 전통의 방법을 이용하여 시간에 따른 SNF의 방사능을 구하고, 계산에 소요되는 시간과 계산 불가능한 오류의 수를 비교하였다. 스플라인 방법을 사용하면 다른 방법을 사용할 때 보다 오류 없이 단시간에 시간에 따른 SNF의 방사능을 얻을 수 있다.
과열영역과 포화영역의 증기표에 대한 상태량의 모델링 연구
이태환,안국찬,박진현 한국기계기술학회 2017 한국기계기술학회지 Vol.19 No.4
The state variables of saturated and superheated region in the steam table were simultaneously modeled using the neural networks. And the results were compared with quadratic spline interpolation and Lagrange interpolation. Two input data without distinguishing parameter were used in the neural networks. For comparison, quadratic spline interpolation method for superheated region and Lagrange interpolation method for saturated region were applied. The overall results revealed that the neural networks were greatly superior to quadratic interpolation method or Lagrange interpolation method.
노이즈가 포함된 과열증기표의 모델링에 신경회로망 적용 타당성에 대한 연구
이태환,박진현 한국기계기술학회 2014 한국기계기술학회지 Vol.16 No.1
The thermodynamic state variables in superheated region of steam table are not wholy obtained by measurements. This means that steam table contains a little error. In this study small error was artificially added to superheated variables and modeled using neural networks. The results were compared with the analysis using quadratic spline interpolation method. By and large the relative errors of variables by neural networks were sufficiently small and similar to or less than those by quadratic spline interpolation method. It was concluded that neural networks could be one good way of modeling for superheated steam table.
신경회로망을 사용한 포화 및 과열 증기표의 동시 모델링
이태환,박진현 한국기계기술학회 2014 한국기계기술학회지 Vol.16 No.6
The steam table in saturated and superheated region was modeled simultaneously using the neural networks. A variable was introduced to distinguish between the saturation and the superheat. The relative errors were compared with the quadratic spline interpolation method. The relative errors by the neural networks were superior to those by the quadratic spline interpolation method over almost all ranges of temperatures and properties. The overall errors in the saturated region were better than those in the superheated region. From the analysis, it was confirmed that the neural networks could be a very powerful tool for simultaneous modeling of superheated and saturated steam table.