Journal Article

Integrated Prediction of Gas Metal Arc Welding Multi-Layer Welding Heat Cycle, Ferrite Fraction, and Joint Hardness of X80 Pipeline Steel

Yang, Die, Zhang, Zhihang, Li, Haonan, Deng, Jun, Yan, Chen, Gao, Yanan, Dong, Zhibo

2025

Overview

X80 pipeline steel is widely used in oil and gas pipelines because of its excellent strength, toughness, and corrosion resistance. It is welded via gas metal arc welding (GMAW), risking high cold crack sensitivities. There is a certain relationship between the joint hardness and cold crack sensitivity of welded joints; thus, predicting the joint hardness is necessary. Considering the inefficiency of welding experiments and the complexity of welding parameters, we designed a set of processes from temperature field analysis to microstructure prediction and finally hardness prediction. Firstly, we calculated the thermal cycle curve during welding through multi-layer welding numerical simulation using the finite element method (FEM). Afterwards, BP neural networks were used to predict the cooling rates in the temperature interval that ferrite nuclears and grows. Introducing the cooling rates to the Leblond function, the ferrite fraction of the joint was given. Based on the predicted ferrite fraction, mapping relationships between joint hardness and the joint ferrite fraction were built using BP neural networks. The results shows that the error during phase fraction prediction is less than 8%, and during joint hardness prediction, it is less than 5%.

• Publisher: MDPI AG
• Subject: Analysis / Arc resistance heating / Back propagation networks / BP neural network / Cooling / Cooling rate / Corrosion resistance / Corrosion resistant steels / Crack sensitivity / Ferrites / Finite element analysis / Finite element method / Friction stir welding / Gas metal arc welding / Gas pipelines / Hardness / High strength low alloy steels / Iron compounds / joint hardness prediction / Low temperature resistance / Machine learning / Mechanical properties / Methods / Microstructure / multi-layer welding numerical simulation / Multilayers / Neural networks / Numerical analysis / Parameter sensitivity / Petroleum pipelines / phase fraction prediction / Phase transitions / Predictions / Simulation / Simulation methods / Software / Structural steels / Temperature distribution / Thermal properties / Thermal simulation / Weld defects / Welded joints / Welding / Welding parameters / X80 pipeline steel