Research on the characteristics of weak magnetic internal detection signals for critical damage in pipeline stress based on density functional theory

Abstract

Pipeline stress-induced critical damage is a primary cause of sudden pipe ruptures. To investigate the characteristics of weak magnetic internal detection signals related to critical damage in pipeline stress, a magneto-mechanical model was developed based on density functional theory. The model could assess the corresponding relationships among the generalized stacking fault energy (GSFE), critical resolved shear stress (CRSS), atomic magnetic moment, and magnetic signals during the critical damage process of the pipeline. The analysis included examining the influential patterns of different stress directions and materials on the magnetic signals associated with critical damage, followed by the systematic experimental verification.The research results indicated that when the crystal dislocation stress exceeded the CRSS, weak magnetic signals could effectively characterize the critical damage induced by stress, accompanying by a sharp variation in magnetic signals observed during critical damage occurrence. Different stress directions lead to varying energy barriers that must be overcome for critical damage, resulting in distinct magnetic signal features. In the {112} plane, the CRSS increased by 11.07 % compared with {11¯0} plane, and the axial magnetic signal during critical damage was elevated by 1.47 % compared with {11¯0} plane. Variances in magnetic signals for critical damage were assessed for steel pipes of different materials due to differences in processing and composition. Under identical conditions, the magnetic signal difference for critical damage in X80 steel plates was 39 % higher than that in X70 steel plates. Additionally, the magnetic signal difference for critical damage in the circumferential weld of X80 was 53 % higher than that in X80. The findings provided a theoretical basis for monitoring and early warning of critical damage states in pipelines.