Published March 2019 | Version v1
Journal article

Application of the modified Bai-Wierzbicki model for the prediction of ductile fracture in pipelines

  • 1. Faculty of Mechanical Engineering, OTH Regensburg, D-93053, Regensburg (Germany)
  • 2. Steel Institute, RWTH Aachen, D-52072, Aachen (Germany)

Description

The complex mechanical and corrosive loads of modern pipeline systems transporting oil, natural gas and CO2 impose steadily increasing requirements on material properties. The majority of current design standards still limit the application of modern high toughness linepipe steels due to the simple specification of material requirements in terms of energy levels from Charpy impact or Battelle Drop-Weight-Tear (BDWT) tests. In consequence, research activities have been conducted recently aiming at developing modified or novel experimental methods for the characterization of the ductile fracture behavior. To quantify the effects of various parameters on fracture behavior and derive suitable correlations, it is necessary to accompany these activities by numerical simulations with appropriate ductile damage models. In this paper, the MBW model is applied to study the structural behavior of pipelines in ductile fracture regime. Due to its precise incorporation of the underlying load conditions, the damage model is successfully used to simulate the slant fracture behavior in Battelle Drop weight tear test specimens and pipe sections. In comparison to ductile damage models applied in former studies, namely the Gurson-Tvergaard-Needleman and Cohesive Zone model, the presented numerical methodology allows for a more detailed investigation of loading, material and geometry effects on fracture and crack arrest behavior of pipelines.

Additional details

Identifiers

DOI
10.1016/j.ijpvp.2019.02.010;
PII
S0308016118303685;

Publishing Information

Journal Title
International Journal of Pressure Vessels and Piping
Journal Volume
171
Journal Page Range
p. 104-116
ISSN
0308-0161
CODEN
PRVPAS

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.