Research Progress on Degradation Mechanism of Mechanical Properties of Materials for Engineering Equipment under Corrosion

XIA Shuhang; WU Jun; AN Jiangfeng; HUANG Gao; YAO Yang

doi:10.7643/issn.1672-9242.2026.06.017

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Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (6) : 187-199. DOI: 10.7643/issn.1672-9242.2026.06.017

Research Progress on Degradation Mechanism of Mechanical Properties of Materials for Engineering Equipment under Corrosion

XIA Shuhang^1,2, WU Jun^1,2,3*, AN Jiangfeng^1,4, HUANG Gao^1,2,4, YAO Yang^1,2,4

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Abstract

The work aims to address the degradation mechanisms of mechanical properties and the service life prediction of engineering equipment materials under corrosion.Firstly,the mechanical failure behaviors and mechanisms of these materials are system atically analyzed, revealing key mechanical degradation mechanisms such as uniform corrosion, pitting corrosion, and stress corrosion cracking. Furthermore, the influence mechanisms of complex morphological defects and multi-field coupling effects on mechanical failures are explored in detail, with focuses on the interactions among multiple corrosion pits and the competing mechanisms between anodic dissolution and hydrogen embrittlement in SCC. Subsequently, the evolution of testing systems from macroscopic mechanical testing to microscopic in-situ characterization and online monitoring is reviewed. The limitations of macroscopic methods, such as static tensile and cyclic fatigue tests, in separating environmental and stress coupling effects are highlighted. The paper also clarifies the inadequacies of in-situ testing techniques, including digital image correlation and nanoindentation, in synchronously acquiring mechanical distortion and micro-electrochemical information, alongside the challenges faced by online monitoring technologies like acoustic emission and optical fiber sensing in the quantitative fusion of heterogeneous data. Additionally, models for predicting mechanical property degradation and remaining life based on fracture mechanics, continuum damage mechanics, and data-driven approaches are summarized, providing theoretical support for geometric equivalent modeling, dynamic damage quantification, and high-precision life assessment of engineering components. Finally, the black-box dilemma associated with purely data-driven models under small-sample conditions is elucidated. It is proposed that constructing a mechanism-data dual-driven model by integrating multi-source monitoring data with Physics-Informed Machine Learning (PIML) represents the future direction for achieving high-precision service life prediction of engineering equipment.

Key words

corrosion / mechanical property degradation / in-situ characterization / prediction model / physics-informed machine learning (PIML)

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XIA Shuhang, WU Jun, AN Jiangfeng, HUANG Gao, YAO Yang. Research Progress on Degradation Mechanism of Mechanical Properties of Materials for Engineering Equipment under Corrosion[J]. Equipment Environmental Engineering. 2026, 23(6): 187-199 https://doi.org/10.7643/issn.1672-9242.2026.06.017

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