Defect-Aware Fatigue Life Framework for Corroded Mooring Chains Integrating Cyclic Plasticity and Crack Growth
- Halid Can YILDIRIM
- Nov 9
- 3 min read
A multistage computational methodology combining the local strain-life approach with fracture mechanics for fatigue life prediction in notched components.
Overview:
This repository presents a comprehensive defect-aware fatigue life prediction framework that integrates short-crack initiation and long-crack propagation phases for corroded mooring chains. The methodology addresses microstructural defects, stress concentrations, and material heterogeneity across different zones, offering a physics-based approach to enhance structural integrity assessments of offshore components.
By combining local strain-life methods with fracture mechanics, this framework accurately predicts total fatigue life (Nf = Ni + Np) while accounting for notch root plasticity, mean stress effects, and microstructural short crack growth. The integration of Newman-Raju and Aursand geometry factors enables precise stress intensity calculations for complex chain geometries.
Key Challenges Addressed
Material heterogeneity: Different material zones (base material, HAZ, weld material) with varying fatigue properties.
Short-long crack transition: Seamless integration of initiation and propagation phases at threshold crack sizes.
Complex geometry: Accurate stress intensity factors for curved round bars and chain-link crown geometries.
Experimental validation: Comprehensive comparison with mooring chain fatigue test data.
Key Features:
Multistage Fatigue Modelling: Combines local strain-life approach (SWT parameter) with Paris law propagation.
Microstructure-Sensitive Initiation: Accounts for material property evolution across different zones.
Advanced Geometry Factors: Incorporates both Newman-Raju and Aursand models for stress intensity calculations.
Experimental Data Integration: Automated visualisation and comparison with extensive fatigue test datasets.
Mean Stress Correction: Walker correction for stress ratio effects on crack propagation.
Material Zones Considered:
The framework accounts for material property variations across different zones:
- Base Material (R4 Steel): High-strength mooring chain steel with calibrated fatigue properties
- Heat-Affected Zone (HAZ): Region with modified microstructure from welding processes
- Weld Material: Filler metal with distinct cyclic stress-strain behaviour
- Corroded Regions: Areas with reduced effective cross-section and stress concentrations
Repository Structure:
`/shot_long_crack.py`: Main fatigue life prediction algorithm implementing multistage methodology
`/SN_data_production.py`: Experimental data visualisation and model comparison tools
`/input_data/`: FEA stress-strain profiles, material properties, and geometry parameters
`/results/`: S-N curves, crack growth predictions, and validation plots
Usage:
1. Run fatigue prediction: Execute `shot_long_crack.py` to generate fatigue life predictions
2. Visualise results: Run `SN_data_production.py` for experimental data comparison and plotting
3. Customise parameters: Modify material properties, geometry factors, and loading conditions as needed
Applications:
Offshore industry: Fatigue life assessment of mooring chains and offshore structures
Predictive maintenance: Remaining life estimation for in-service components
Design optimisation: Material selection and geometry optimisation for fatigue resistance
Industry standards: Data-driven approach for fatigue design criteria development
Validation:
The framework has been validated against:
- Experimental S-N data for R4 mooring chain steel
- Multiple loading conditions and stress ratios
- Various geometric configurations and notch geometries
Contributions:
Contributions to model enhancement, experimental validation, or industrial applications are welcome. Please contact the authors for collaboration opportunities.
Citation:
If this work supports your research, please cite the original paper:
Fernández de Castro, A., & Yıldırım, H.C. (2025). "A defect-aware fatigue life framework for corroded mooring chains integrating cyclic plasticity and crack growth." International Journal of Fatigue, 109386. https://doi.org/10.1016/j.ijfatigue.2025.109386
@article{DECASTRO2025109386,
title = {A defect-aware fatigue life framework for corroded mooring chains integrating cyclic plasticity and crack growth},
journal = {International Journal of Fatigue},
pages = {109386},
year = {2025},
issn = {0142-1123},
doi = {https://doi.org/10.1016/j.ijfatigue.2025.109386},
url = {https://www.sciencedirect.com/science/article/pii/S0142112325005833},
author = {Alejandro Fernández {de Castro} and Halid Can Yıldırım},
keywords = {Mooring chains, Fatigue life prediction, Fracture mechanics, Cyclic plasticity, Crack growth, Offshore structures},
abstract = {Current design approaches for offshore mooring chains primarily rely on simplified corrosion allowances that may fail to capture the severe fatigue degradation caused by very localised pitting and preferential weld corrosion (PWC). This paper presents a novel, defect-aware fatigue assessment framework that integrates finite element analysis, cyclic plasticity, and fracture mechanics to deliver high-fidelity life predictions for the experimentally tested corroded chains. The methodology explicitly models pitting at the crown and trench-like PWC grooves at the weld-line as geometric stress concentrators. A mechanics-based algorithm, combining strain-life initiation and Paris-law propagation, is applied using local stress–strain fields from dedicated FE models. The framework is validated against a harmonised dataset of full-scale S-N tests from new and corroded Grade R4 chains. Results demonstrate that the critical failure location shifts to the crown under pitting corrosion, and the model accurately predicts the associated life reduction, which may be significantly under-estimated by the current simplified methods. In particular, the predicted fatigue strength for corroded chains was up to a factor of two lower than that suggested by the DNV design curve, highlighting the importance of defect-aware modelling in safety-critical design. This work provides a robust, physics-based tool for the integrity management of critical offshore assets, moving beyond empirical S-N curves.}
}
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