유전자 알고리즘을 이용한 시스템 최적 부분구조화 = System Target Propagation to Model Order Reduction of a Beam Structure Using Genetic Algorithm

다국어 초록 (Multilingual Abstract)

In many engineering problems, the dynamic substructuring can be useful to analyze complex structures which made with manysubstructures, such as aircrafts and automotive vehicles. It was originally intended as a method to simplify the engineering problem. Thepowerful advantage to this is that computational efficiency dramatically increases with eliminating unnecessary degrees-of-freedom of thesystem and the system targets are concurrently satisfied. Craig-Bampton method has been widely used for the linear system reduction.
Recently, multi-level optimization (such as target cascading), which propagates the system-level targets to the subsystem-level targets, hasbeen widely utilized. To this concept, the genetic algorithm which one of the global optimization technique has been utilized to thesubstructure optimization. The number of internal modes for each substructure can be obtained by the genetic algorithm. Simultaneously, thereduced system meets the top-level targets. In this paper, various numerical examples are tested to verify this concept.

국문 초록 (Abstract)

부분구조화 기법은 자유도가 많고 복잡한 구조물의 유한요소 해석 모델 단순화에 효율적으로 적용될 수 있는 기법이다. 대표적으로 선형 문제에 대해서는 Craig-Bampton method 등이 있다. Craig-Bampton method는 경계 요소를 제외한 나머지 요소의 불필요한 자유도를 제거함으로써 선형 구조물의 축소를 수행한다. 최근에는 부분구조화 기법과 더불어 구조물의 최적설계를 위해 멀티레벨 최적화 기법이 많이 활용되고 있다. 시스템의 목표를 달성하기 위해 각 부구조에 새로운 목표를 할당하는 기법이다. 본 연구에서는 유전자알고리즘을 이용하여 시스템 목표 달성을 위한 각 부구조별 내부 자유도 개수를 새로운 목표로 할당하고 최적화를 수행하였다. 최적화 절차로부터 도출된 부구조별 내부 자유도 개수를 이용하여 시스템의 축소를 수행하였다. 다양한 수치예제들을 통해 축소 모델에대한 결과를 확인하였으며, 90% 이상의 정확도를 가지는 것을 확인하였다.

참고문헌 (Reference)

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