Session: 03-03-03 Dent Modeling and API 1183 I

Paper Number: 133905

133905 - Improvements to B31.8 Dent Strain Estimation and Assessment of Dent
Formation Induced Cracking 

Abstract: 

Local plastic deformation associated with the dent formation can potentially cause ductile damage leading to cracks. Plastic strain is considered as a key indicator to dent formation-induced cracking. The estimation of local plastic strain in a dent is mainly based on the calculation of dent profile curvatures. The ASME B31.8 effective strain equations provide a basis to convert the curvature into strain.         

In this paper, a variety of methods used to estimate dent profile curvatures were evaluated for calculating plastic strain. Hypothetical dent profiles generated from FEA simulations were used for the evaluation. The plastic strains obtained by using the B31.8 equations were compared with the FEA results on equivalent plastic strains for all the simulated dent profiles. It was shown that the estimation of plastic strain was sensitive to the methods used for extracting the dent profile curvatures. A method based on the 4^th order polynomial curve fitting on a total of 9 points selected near the dent apex was shown to provide more consistent results compared with other methods investigated in the present paper.

Unconstrained dents have posed a challenge to use the B31.8 effective strain equations to estimate the plastic strain. The measured dent profiles from pipeline inline inspection (ILI) for an unconstrained dent can be significantly different from the indentation dent profiles due to plastic re-rounding. The estimated plastic strains based on the current dent shapes after re-rounding with the B31.8 equation display a significant scatter compared with the FEA simulation results. A regression model was developed to improve the strain estimates based on the B31.8 equations using the current dent profiles after re-rounding. The regression model was intended to correct the strain estimates from the B31.8 equations by including the current dent geometries and pipe internal pressure. Trained with FEA simulation results for unconstrained dents, the regression equation was shown to significantly improve the strain estimates compared with the FEA results.

Presenting Author: Huang Tang Integrity Risk Assessment Specialist

Presenting Author Biography: Huang has over 15 years of experience in oil and gas industry. He joined Enbridge in 2021 as a pipeline integrity risk assessment specialist. His work has been focused on dent strain and fracture assessment with machine learning and FEA simulations and MAOP reconfirmation. Before joining Enbridge, he was with ExxonMobil and has over 13 years of experience with the company. At ExxonMobil, he worked heavily on the research and development of strain-based pipeline design technology, fitness for service assessment and hydrogen embrittlement and sour service. Huang Tang received his bachelor’s degree in mechanical engineering from Tsinghua University and his Ph.D. degree in civil engineering from Carnegie Mellon University. He conducted postdoctoral research at MIT and Northwestern University with a focus on advanced modeling of mechanical behavior of materials.

Authors:

Huang Tang Integrity Risk Assessment Specialist
Guanbo Zheng Enbridge
Jialin Sun Enbridge
Derek Kohlenberg Enbridge
Martin Di Blasi Enbridge