Developments in Local Approach methodology with application to the analysis/re-analysis of the NESC-1 PTS benchmark experiment

摘要

Local Approach methods have received considerable attention in recent years as a complementary approach to structural integrity assessment. These approaches are based on the application of micro-mechanistic models of failure in which the stress, strain and 'damage' local to the crack-tip are related to the critical conditions required to initiate/propagate fracture. The models are calibrated in terms of material parameters that are deemed fully transferable and derived using a combination of reference test data and supporting stress analysis. Once calibrated, using small-scale test date, the models are assumed independent on geometry and loading configuration. For a given failure mechanism, the model parameters may be used in the assessment of a structure fabricated from the same material (for appropriate temperatures, loading rates, etc).The paper describes the work initially undertaken in relation the NESC-1 (Network for Evaluating Steel components) spinning cylinder test, in order to validate the application of Local Approach methods for the case of PTS loading. The predicted amount of pre-cleavage ductile tearing and the timing of the subsequent cleavage event are compared with the observed fracture behaviour of the defect.The paper then highlights several areas in which Local Approach methodology has been developed since the initial work on PTS. These include.· Calibration of the cleavage model across a range of temperatures and constraint states.· Treatment of 3D defects.· Reference to hydrostatic stress in cleavage fracture predictions.· Simplification and standardisation of techniques for more routine use in integrity assessments.The paper concludes that results from large-scale structural experiments, such as the NESC-1 spinning cylinder test, will be of lasting value in validating developments in Local Approach methodology and other advanced methods of fracture assessment. This is particularly true in the author's current work that seeks to achieve an overall simplification in methodology, without sacrificing predictive accuracy.