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학술논문한국산학기술학회논문지2013.10 발행KCI 피인용 5

In-Plane Buckling Analysis of Asymmetric Curved Beam Using DQM

In-Plane Buckling Analysis of Asymmetric Curved Beam Using DQM

강기준(호서대학교); 박차식(호서대학교)

14권 10호, 4706~4712쪽

초록

One of the efficient procedures for the solution of partial differential equations is the method of differential quadrature. This method has been applied to a large number of cases to circumvent the difficulties of programming complex algorithms for the computer, as well as excessive use of storage due to conditions of complex geometry and loading. Under in-plane uniform distributed load, the buckling of asymmetric curved beam with varying cross section is analyzed by using differential quadrature method (DQM). Critical load due to diverse cross section variation and opening angle is calculated. Analysis result of DQM is compared with the result of exact analytic solution. As DQM is used with small grid points, exact analysis result is shown. New result according to diverse cross section variation is also suggested.

Abstract

One of the efficient procedures for the solution of partial differential equations is the method of differential quadrature. This method has been applied to a large number of cases to circumvent the difficulties of programming complex algorithms for the computer, as well as excessive use of storage due to conditions of complex geometry and loading. Under in-plane uniform distributed load, the buckling of asymmetric curved beam with varying cross section is analyzed by using differential quadrature method (DQM). Critical load due to diverse cross section variation and opening angle is calculated. Analysis result of DQM is compared with the result of exact analytic solution. As DQM is used with small grid points, exact analysis result is shown. New result according to diverse cross section variation is also suggested.

발행기관:
한국산학기술학회
DOI:
http://dx.doi.org/10.5762/KAIS.2013.14.10.4706
분류:
공학일반

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In-Plane Buckling Analysis of Asymmetric Curved Beam Using DQM | 한국산학기술학회논문지 2013 | AskLaw | 애스크로 AI