Simulation of Ratcheting Behavior and Prediction of the Fatigue Life of HRB400 Steel Based on Crystal Plasticity Analysis

ABSTRACT In this study, the ratcheting behavior of HRB400 steel throughout its entire life cycle was investigated through experimental tests and crystal plasticity numerical simulations. The relationship between fatigue life and the evolution of grain–level deformation inhomogeneity was explored. The results demonstrate that strain/stress amplitude, mean stress, peak stress, and yield strength significantly influence the cyclic hardening/softening characteristics and ratcheting behavior during the initial loading stage. These effects were quantified using a back stress evolution function that incorporates both peak stress and stress amplitude. Furthermore, the statistical standard deviation of strain, serving as an indicator of deformation inhomogeneity, was established as a fatigue indicator parameter (FIP). Subsequently, the method for predicting the lives of the material corresponding to different types of fatigue failures was developed. This method was successfully applied to low–cycle fatigue (LCF) life prediction for specimens subjected to controlled strain/stress loading cycles, with its validity confirmed through experimental measurements.

Authors

Institutions

Publication Details

Journal
Fatigue & Fracture of Engineering Materials & Structures
Published
2025-08-10
DOI
https://doi.org/10.1111/ffe.70050
Primary Topic
Fatigue and fracture mechanics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulation of Ratcheting Behavior and Prediction of the Fatigue Life of HRB400 Steel Based on Crystal Plasticity Analysis

Yong Yang, Lili Jin, Xinlai Wei, Ke‐Shi Zhang et al.
Fatigue & Fracture of Engineering Materials & Structures
Fatigue and fracture mechanics
article

Simulation of Ratcheting Behavior and Prediction of the Fatigue Life of HRB400 Steel Based on Crystal Plasticity Analysis

Yong Yang, Lili Jin, Xinlai Wei, Ke‐Shi Zhang, Bin Zeng
article en

Abstract

ABSTRACT In this study, the ratcheting behavior of HRB400 steel throughout its entire life cycle was investigated through experimental tests and crystal plasticity numerical simulations. The relationship between fatigue life and the evolution of grain–level deformation inhomogeneity was explored. The results demonstrate that strain/stress amplitude, mean stress, peak stress, and yield strength significantly influence the cyclic hardening/softening characteristics and ratcheting behavior during the initial loading stage. These effects were quantified using a back stress evolution function that incorporates both peak stress and stress amplitude. Furthermore, the statistical standard deviation of strain, serving as an indicator of deformation inhomogeneity, was established as a fatigue indicator parameter (FIP). Subsequently, the method for predicting the lives of the material corresponding to different types of fatigue failures was developed. This method was successfully applied to low–cycle fatigue (LCF) life prediction for specimens subjected to controlled strain/stress loading cycles, with its validity confirmed through experimental measurements.

Fatigue & Fracture of Engineering Materials & Structures
Foshan University (CN), Guangxi University (CN), Guangxi Transportation Research Institute (CN)
National Natural Science Foundation of China, Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, Systematic Project of Guangxi Key Laboratory of Disaster Prevention and Structural Safety
Openalex Percentile: Top 77%
Fatigue and fracture mechanics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.