Low-Cycle Fatigue Life Prediction of HY-80 T-joint Welds by Plastic-Stress Correction

Low-cycle fatigue (LCF) life assessment typically involves complex procedures, such as acquiring material properties through cyclic stress-strain tests followed by strain-controlled fatigue tests. In this study, a practical method is proposed to predict the LCF life of high-strength steel T-joint welds using only minimal material properties, such as limited fatigue data and tensile strength.</br>First, stress-controlled fatigue test data with mean stress was converted to fully-reversed (R = -1) conditions using the Goodman equation. An initial S-N curve was then constructed by extrapolating a virtual data point using the tensile strength. Subsequently, the stress in the low-cycle region was corrected by applying a plasticity correction factor derived from nonlinear finite element analysis (FEA), and the fatigue life was predicted accordingly.</br>For validation, the results of the proposed method were compared with a baseline established from the Coffin-Manson and Ramberg-Osgood relations. The results showed a strong agreement, with a prediction error of less than 6.6% at 10,000 cycles, confirming the model’s validity. This method is expected to be useful for the rapid and simple assessment of fatigue performance in high-strength steel welds when data is limited, such as in early design stages.

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Publication Details

Journal
Journal of Welding and Joining
Published
2025-12-30
DOI
https://doi.org/10.5781/jwj.2025.43.6.8
Primary Topic
Fatigue and fracture mechanics
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Cycle Fatigue Life Prediction of HY-80 T-joint Welds by Plastic-Stress Correction

Jihoon Kim, Han-Min Bang, Myung-Hyun Kim
Journal of Welding and Joining
Fatigue and fracture mechanics
article

Low-Cycle Fatigue Life Prediction of HY-80 T-joint Welds by Plastic-Stress Correction

Jihoon Kim, Han-Min Bang, Myung-Hyun Kim
article en

Abstract

Low-cycle fatigue (LCF) life assessment typically involves complex procedures, such as acquiring material properties through cyclic stress-strain tests followed by strain-controlled fatigue tests. In this study, a practical method is proposed to predict the LCF life of high-strength steel T-joint welds using only minimal material properties, such as limited fatigue data and tensile strength.</br>First, stress-controlled fatigue test data with mean stress was converted to fully-reversed (R = -1) conditions using the Goodman equation. An initial S-N curve was then constructed by extrapolating a virtual data point using the tensile strength. Subsequently, the stress in the low-cycle region was corrected by applying a plasticity correction factor derived from nonlinear finite element analysis (FEA), and the fatigue life was predicted accordingly.</br>For validation, the results of the proposed method were compared with a baseline established from the Coffin-Manson and Ramberg-Osgood relations. The results showed a strong agreement, with a prediction error of less than 6.6% at 10,000 cycles, confirming the model’s validity. This method is expected to be useful for the rapid and simple assessment of fatigue performance in high-strength steel welds when data is limited, such as in early design stages.

Journal of Welding and JoiningVol. 43(6)
Pusan National University
Responsible consumption and production
Openalex Percentile: Top 41%
Fatigue and fracture mechanics
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