Journals / Politeknik Dergisi / 2020 / Cilt: 23 - Sayı: 1

Large Deflection Analysis of Prismatic Cantilever Beam Comparatively by Using Combing Method and Iterative DQM

Pages
111–120
DOI
—

Abstract

There is no exactly analytical solution for the large deflection problem of prismatic cantilever beams under general loading conditions. In the case of considering a non-prismatic cantilever beam, the difficulty of the larger deflection problem is increased. In this study, the comparison of the Iterative Differential Quadrature Method (I-DQM) and the Combining Method (CM) was performed. Numerical solution of the large deflection problem was separately performed with both the I-DQM and the CM for prismatic cantilever beams. The obtaining results show that both of these methods gave more accurate solutions compared with a reliable semi-analytic method which was introduced by Dado and Sadder (2005). Besides, it was demonstrated that the I-DQM provided a more wide-range solution than the CM.

Özet

There is no exactly analytical solution for the large deflection problem of prismatic cantilever beams under general loading conditions. In the case of considering a non-prismatic cantilever beam, the difficulty of the larger deflection problem is increased. In this study, the comparison of the Iterative Differential Quadrature Method (I-DQM) and the Combining Method (CM) was performed. Numerical solution of the large deflection problem was separately performed with both the I-DQM and the CM for prismatic cantilever beams. The obtaining results show that both of these methods gave more accurate solutions compared with a reliable semi-analytic method which was introduced by Dado and Sadder (2005). Besides, it was demonstrated that the I-DQM provided a more wide-range solution than the CM.

Keywords: Large deflection, iterative differential quadrature method, combining method, nonlinear simulation, cantilever prismatic beam

Large Deflection Analysis of Prismatic Cantilever Beam Comparatively by Using Combing Method and Iterative DQM — AJIndex