A TSC model for pipelines girth weld considering variations in toughness across different regions

Abstract

The tensile strain capacity (TSC) model serves as a robust tool for assessing the integrity of pipeline girth welds and associated defects. However, existing TSC models predominantly rely on static crack methods, making it challenging to capture the effects of crack propagation and fracture toughness on the load-bearing capacity of pipeline girth welds. Therefore, this study investigated the initiation and propagation of pipeline cracks using the Gurson-Tvergaard-Needleman (GTN) model. A novel method was introduced for the first time to characterize toughness variations across different regions of pipeline girth welds, employing Charpy impact energy. The study examined how differences in strength matching and toughness affect crack initiation location, and proposed a criterion for evaluating remote strain at the point of crack wall penetration. Based on this, the influence of crack location and size on the load-bearing capacity of pipeline girth welds was analyzed. Additionally, the effects of strength matching, the degree of softening in the heat-affected zone (HAZ), and toughness differences on load-bearing capacity were investigated. The study also proposed a novel predictive formula for tensile strain capacity, incorporating these factors. Results indicate that toughness significantly influences crack initiation location more than strength matching or HAZ softening, with cracks tending to initiate at regions of lower toughness even if strength is higher. Pipeline load-bearing capacity was found to be lower when crack initiation occurred within the HAZ. Moreover, load-bearing capacity increased with the strength matching coefficient, HAZ matching coefficient, and toughness matching coefficient, with this relationship fitting a quadratic function. Conversely, the load-bearing capacity of pipeline girth welds is inversely proportional to crack depth and length. The newly developed predictive formula demonstrated a normal distribution error margin within 10 %, confirming its accuracy. These findings are valuable for addressing TSC conservatism and expanding its applicability.