• 제목/요약/키워드: Hermite collocation method

검색결과 4건 처리시간 0.016초

부정류 해석을 위한 Hermite-Collocation 기법의 적용 (Application of Hermite-Collocation Method for Unsteady Flow Analysis)

  • 한건연;이을래;박재홍
    • 한국수자원학회논문집
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    • 제32권3호
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    • pp.237-246
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    • 1999
  • 자유수면 흐름의 모의를 위한 유한요소모형이 동수역학적 흐름방정식과 collocation 유한요소법에 의해 모의하였다. collocation 기법은 Hermite 다항식을 가진 접합점에서 적용이 되며, 메크릭스 방정식은 skyline 기법에 의해 해석하였다. 본 연구 모형은 마찰이 없는 수평수로에서의 정상도수, 비선형 표면전파 그리고 댐 파괴해석에 적용하였다. 계산결과 Bubnov-Galerkin 과 Petrov-Galerkin 기법과 비교하였다. 실제하천에 대한 적용성을 검토하기 위해서 북한강 유역에 적용하여 해석하였는데, 계산결과는 유량수문곡선에 있어서 기존의 DWOPER 모형의 결과와 일치하였다. Collocation 기법은 개수로 흐름에서의 점변 및 급변 부정류흐름을 모의하기 위해서 적절한 기법임을 확인할 수 있었다.

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SOLVING PARTIAL DIFFERENTIAL ALGEBRAIC EQUATIONS BY COLLOCATION AND RADIAL BASIS FUNCTIONS

  • Bao, Wendi;Song, Yongzhong
    • Journal of applied mathematics & informatics
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    • 제30권5_6호
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    • pp.951-969
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    • 2012
  • In this paper, we propose a class of meshless collocation approaches for the solution of time dependent partial differential algebraic equations (PDAEs) in terms of a radial basis function interpolation numerical scheme. Kansa's method and the Hermite collocation method (HCM) for PDAEs are given. A sensitivity analysis of the solutions from different shape parameter c is obtained by numerical experiments. With use of the random collocation points, we have obtain the more accurate solution by the methods than those by the finite difference method for the PDAEs with index-2, i.e, we avoid the influence from an index jump of PDAEs in some degree. Several numerical experiments show that the methods are efficient.

EXCEL Tools for Geotechnical Reliability Analysis

  • Phoon, Kok-Kwang
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2008년도 추계 학술발표회
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    • pp.375-394
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    • 2008
  • This paper discusses two user-friendly reliability techniques that could be implemented easily using the ubiquitous EXCEL. The techniques are First-Order Reliability Method with non-Gaussian random variables expressed using Hermite polynomials and collocation-based stochastic response surface method. It is believed that ease of implementation would popularize use of reliability-based design in practice.

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A comparative study of three collocation point methods for odd order stochastic response surface method

  • Li, Dian-Qing;Jiang, Shui-Hua;Cheng, Yong-Gang;Zhou, Chuang-Bing
    • Structural Engineering and Mechanics
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    • 제45권5호
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    • pp.595-611
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    • 2013
  • This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.