Original Article
  • Fatigue Life Prediction of Laminated Composite Materials by Multiple S-N Curves and Lamina-Level Failure Criteria
  • Hangil You*, Dongwon Ha*, Young Sik Joo**, Gun Jin Yun*†

  • * Department of Aerospace Engineering, Seoul National University, Seoul 08826, Korea
    ** Aerospace Technology Research Institute, Agency for Defense

  • This article is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In this paper, we present a fatigue life prediction methodology using multiple S-N curves according to the different stress states of laminated composites. The stress states of the plies of the laminated composites are classified into five modes: longitudinal tension or compression and transverse tension or compression, and shear according to the maximum stress criterion and Puck's criterion with a scaling factor K. This methodology has advantages in computational cost, and it can also consider microstructural characteristics of the composites by applying different S-N curves. The S-N curves for the fatigue analysis are obtained by experimental fatigue test. The proposed methodol is implemented into commercial software, ABAQUS user material subroutine and therefore, the fatigue analysis is conducted using the structural analysis results. The finite element (FE) simulation results are presented for unidirectional composites with and without open-hole. The FE simulation results show that the stress condition is different depending on the fiber orientation of the unidirectional composite, so the fatigue life is calculated with different S-N curves


Keywords: Composite Fatigue analysis, Puck's criterion, Unidirectional Composite, Multiple S-N curves

This Article

Correspondence to

  • Gun Jin Yun
  • Department of Aerospace Engineering, Seoul National University, Seoul 08826, Korea

  • E-mail: gunjin.yun@snu.ac.kr