The problem of a beam containing a semi-elliptical surface crack and subjected to tension or bending loading is investigated. The stress-intensity factor along the crack front can be calculated assuming a model with finite strips arranged in series and parallel. Several cases are analysed varying th
Stress intensity factors forV-notched strip under tension or in-plane bending
β Scribed by Dai-Heng Chen
- Book ID
- 104614576
- Publisher
- Springer Netherlands
- Year
- 1995
- Tongue
- English
- Weight
- 760 KB
- Volume
- 70
- Category
- Article
- ISSN
- 1573-2673
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β¦ Synopsis
The singular stress field around a sharp notch tip is expressed as a sum of two independent fields: a symmetric field with a stress singularity l/r'-x1 and a skew-symmetric field with a stress singularity l/r'-x2. The intensities of the symmetric and skew-symmetric singular stress fields are defined in terms of constants Kt and Ku, respectively. In this study, a plane problem of a strip with single or double edge notches under tension or in-plane bending is considered. The bisector of the notch may be inclined to the edge, so that the two singular stress fields with different singularities may be created simultaneously at the notch tip. The body force method is used to calculate the stress intensity factors KI and Kn. In numerical analysis, basic density functions of the body forces are introduced to characterize the stress singularity at the notch tip. The advantages of this technique are the high accuracy of results, due to the smoothness of the unknown weight functions, and the presence of the direct relation between the values of Kt and Kn and the values of unknown weight functions. The stress intensity factors are systematically calculated for the various geometrical conditions.
π SIMILAR VOLUMES
The fractal-like finite element method (FFEM) is extended to compute the stress intensity factors (SIFs) of double-edge-/centre-notched plates subject to out-of-plane shear or tension loading conditions. In the FFEM, the use of global interpolation functions reduces the large number of unknowns in a