Publications

Non-destructive detection methods can reliably certify that gas transfer system (GTS) reservoirs do not have cracks larger than 5%-10% of the wall thickness. To determine the acceptability of a reservoir design, analysis must show that short cracks will not adversely affect the reservoir behavior. This is commonly done via calculation of the J-Integral, which represents the energetic driving force acting to propagate an existing crack in a continuous medium. J is then compared against a material's fracture toughness (J{sub c}) to determine whether crack propagation will occur. While the quantification of the J-Integral is well established for long cracks, its validity for short cracks is uncertain. This report presents the results from a Sandia National Laboratories project to evaluate a methodology for performing J-Integral evaluations in conjunction with its finite element analysis capabilities. Simulations were performed to verify the operation of a post-processing code (J3D) and to assess the accuracy of this code and our analysis tools against companion fracture experiments for 2- and 3-dimensional geometry specimens. Evaluation is done for specimens composed of 21-6-9 stainless steel, some of which were exposed to a hydrogen environment, for both long and short cracks.

Abstract not provided.

The mechanical properties of some materials (Cu, Ni, Ag, etc.) have been shown to develop strong dependence on the geometric dimensions, resulting in a size effect. Several theories have been proposed to model size effects, but have been based on very few experiments conducted at appropriate scales. Some experimental results implied that size effects are caused by increasing strain gradients and have been used to confirm many strain gradient theories. On the other hand, some recent experiments show that a size effect exists in the absence of strain gradients. This report describes a brief analytical and experimental study trying to clarify the material and experimental issues surrounding the most influential size-effect experiments by Fleck et al (1994). This effort is to understand size effects intended to further develop predictive models.