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3D fractal modeling of non-uniform corrosion in steel pipes: Failure behavior analysis and structural integrity assessment

Author

Listed:
  • Li, Pengju
  • Li, Bin
  • Fang, Hongyuan
  • Du, Xueming
  • Wang, Niannian
  • Zang, Quansheng
  • Di, Danyang

Abstract

To address the limitations of conventional idealized geometric assumptions in evaluating the failure pressure of corroded steel pipes, this study proposes an integrated methodology combining three-dimensional (3D) fractal theory with finite element (FE) modeling to characterize the mechanical behavior of random non-uniform corrosion defects. A random non-uniform corrosion pipe model was developed by reconstructing corrosion morphologies using the Weierstrass-Mandelbrot (W-M) fractal function within a Python-ABAQUS collaborative framework, incorporating fractal dimension (Dn), spatial frequency (γ), and scale coefficient (Cn). The model's reliability was validated through full-scale burst tests. Systematic quantification revealed the correlation between geometric parameters of single-point defects, spacing of double-point defects, and failure behavior. The results demonstrate that under single-point corrosion conditions, increasing the defect length to 180 mm and depth to 0.8t reduces failure pressure by 15.99 % and 23.66 %, respectively. Conversely, widening the corrosion angle to 40° reduces failure pressure by only 7.85 % through stress dispersion effects. For double-point corrosion interaction, longitudinal spacing exerts a significantly stronger influence on defect coupling than circumferential spacing. Critical spacings (1.5Dt for longitudinal alignment and 0.16πD for circumferential alignment) effectively isolate interaction effects. This study establishes a systematic correlation framework between fractal characteristics and mechanical responses, advancing a theoretical paradigm for the reliability assessment of corroded pipelines.

Suggested Citation

  • Li, Pengju & Li, Bin & Fang, Hongyuan & Du, Xueming & Wang, Niannian & Zang, Quansheng & Di, Danyang, 2025. "3D fractal modeling of non-uniform corrosion in steel pipes: Failure behavior analysis and structural integrity assessment," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    • Handle: RePEc:eee:reensy:v:261:y:2025:i:c:s0951832025003126
    DOI: 10.1016/j.ress.2025.111111
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    References listed on IDEAS

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    1. Miao, Xingyuan & Zhao, Hong, 2023. "Novel method for residual strength prediction of defective pipelines based on HTLBO-DELM model," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Zhang, Shuai & Li, Yingjun & Wang, Guicong & Qi, Zhenguang & Zhou, Yuanqin, 2024. "A novel method for calculating the fractal dimension of three-dimensional surface topography on machined surfaces," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    3. Amaya-Gómez, Rafael & Sánchez-Silva, Mauricio & Muñoz, Felipe & Schoefs, Franck & Bastidas-Arteaga, Emilio, 2024. "Spatial characterization and simulation of new defects in corroded pipeline based on In-Line Inspections," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Huang, Yunfei & Qin, Guojin & Yang, Ming & Nogal, Maria, 2025. "Dynamic quantitative assessment of service resilience for long-distance energy pipelines under corrosion," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    5. Miao, Xingyuan & Zhao, Hong, 2024. "Corroded submarine pipeline degradation prediction based on theory-guided IMOSOA-EL model," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    6. Zhang, Zhiwei & Li, Songling & Wang, Huajie & Qian, Hongliang & Gong, Changqing & Wu, Qiongyao & Fan, Feng, 2025. "A study of neural network-based evaluation methods for pipelines with multiple corrosive regions," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    7. Woldesellasse, Haile & Tesfamariam, Solomon, 2023. "Consequence assessment of gas pipeline failure caused by external pitting corrosion using an integrated Bayesian belief network and GIS model: Application with Alberta pipeline," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    8. Iannacone, Leandro & Gardoni, Paolo, 2024. "Modeling deterioration and predicting remaining useful life using stochastic differential equations," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    9. Jiang, Fengyuan & Dong, Sheng, 2024. "Probabilistic-based burst failure mechanism analysis and risk assessment of pipelines with random non-uniform corrosion defects, considering the interacting effects," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Zhang, Tieyao & Shuai, Jian & Shuai, Yi & Hua, Luoyi & Xu, Kui & Xie, Dong & Mei, Yuan, 2023. "Efficient prediction method of triple failure pressure for corroded pipelines under complex loads based on a backpropagation neural network," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
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