한국수자원학회논문집 (Journal of Korea Water Resources Association)

한국수자원학회 (Korea Water Resources Association)
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2차원 흐름해석모형의 매개변수 최적조합결정 자동화 알고리즘의 개발과 적용

Development and application of automation algorithm for optimal parameter combination in two-dimensional flow analysis model

  • 안세혁 (인천대학교 안전공학과) ;
  • 신은택 (인천대학교 안전공학과) ;
  • 송창근 (인천대학교 안전공학과) ;
  • 박성원 (인천대학교 도시환경공학부)
  • An, Sehyuck (Department of Safety Engineering, Incheon National University) ;
  • Shin, Eun-taek (Department of Safety Engineering, Incheon National University) ;
  • Song, Chang Geun (Department of Safety Engineering, Incheon National University) ;
  • Park, Sungwon (Department of Civil and Environmental Engineering, Incheon National University)
  • 투고 : 2023.08.30
  • 심사 : 2023.10.04
  • 발행 : 2023.12.31
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초록

천수방정식 기반 흐름해석모형은 하천 및 수로에서의 흐름을 수평 2차원적으로 수치모의하는데 활용되며 매개변수인 와점성계수와 조도계수에 큰 영향을 받는다. 따라서 적절한 매개변수의 선택은 흐름특성을 정확하게 모사하기 위해 매우 중요하다. 본 연구에서는 2차원 흐름해석에 적용되는 매개변수의 최적조합을 찾기 위한 자동화 알고리즘을 개발하고 적용하였다. 기존연구에서 2차원 흐름해석모형을 적용하는 경우 매개변수의 선정에 있어 경험적인 방법을 사용하여 최적의 매개변수를 찾는데 어려움이 있었다. 따라서 본 연구에서는 실험결과를 활용하여 다양한 매개변수의 조합에 따른 오차를 추적하고, 매개변수의 최적조합을 결정할 수 있는 알고리즘을 Python 언어를 이용하여 개발하고 적용하였다. 자동화 알고리즘은 121(11×11)개의 매개변수 조합에 따른 2차원 흐름해석결과 중 유속모의결과의 오차값을 비교하여 가장 정확한 조합을 손쉽게 결정하도록 구성되었다. 오차가 가장 작은 매개변수의 최적조합을 자동화 알고리즘의 적용을 통해 신속하고 간단하게 결정할 수 있다는 측면에서 높은 활용가치가 있을 것으로 기대된다.

Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.

키워드

과제정보

본 결과물은 환경부의 재원으로 한국환경산업기술원의 기후위기대응 홍수방어능력 기술개발사업의 지원을 받아 연구 되었습니다(2022003470001).

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