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      효율적 유한 요소 생성을 위한 미소 기하 특징 소거

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      https://www.riss.kr/link?id=E686398

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      다국어 초록 (Multilingual Abstract)

      Given the widespread use of the Finite Element Method in strength analysis, automatic mesh genera tion is an important component in the computer-aided design of parts and assemblies. For a given resolution of geometric accuracy, the purpose of mesh ge...

      Given the widespread use of the Finite Element Method in strength analysis, automatic mesh genera tion is an important component in the computer-aided design of parts and assemblies. For a given resolution of geometric accuracy, the purpose of mesh generators is to discretize the continuous model of a part within this error limit. Sticking to this condition often produces many small elements around small features in spite that these regions are usually of little interest and computer resources are thus wasted. Therefore, it is desirable to selectively suppress small features from the model before discretization. This can be achieved by low-pass filtering a CAD model A spatial function of one dimension higher than the model of interest is represented using the Fourier basis functions and the region where the function yields a value greater than a prescribed value is considered as the extent of a shape. Subsequently, the spatial function is low-pass filtered, yielding a shape without the small features. As an undesirable effect to this operation, all sharp corners are rounded. Preservation of sharp corners is important since stress concentrations might occur there. This is why the LPF(low-pass filtered) model can not be directly used instead, the distances of the boundary elements of the original shape from the LPF model are calculated and those that are far from the LPF model are identified and removed. It is shown that the number of mesh elements generated on the simplified model is much less than that of the original model.

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      목차 (Table of Contents)

      • Abstract
      • 1. 서론
      • 2. 관련 연구
      • Abstract
      • 1. 서론
      • 2. 관련 연구
      • 3. 알고리즘
      • 4. 결과
      • 5. 결론
      • 감사의 글
      • 참고문헌
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