Key Takeaways & Executive Findings
- •• • At 60 days of NSS exposure, the 45° inclined specimen's F1 surface exhibited average rust layer thickness and average pit depth 45.79% and 54.78% greater than the 0° horizontal specimen, respectively—quantifying the penalty for geometries that prevent protective electrolyte film formation and directly informing inspection intervals for inclined structural members. • • The 3D-CA corrosion model reproduced experimental pit morphology and depth with error below 5%, and simulated pit depth distributions followed a Weibull function, establishing a validated numerical tool for predicting spatially non-uniform corrosion damage without destructive testing. • • Spatial orientation dictates corrosion hierarchy: at 0° and 45°, upper flange > web > lower flange; at 90°, W1 > flanges > W2. This inversion at 90° means that inspection protocols derived from flat-plate data will systematically misallocate resources across H-section surfaces. • • The model's exclusion of coupled stress and external loading defines its current operational boundary; extrapolation to service conditions involving corrosion-fatigue interaction requires multi-scale extension, a limitation that must be accounted for in remaining-life assessments of load-bearing H-shaped steel components.
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Abstract
H-shaped steel components are ubiquitous in steel structures, yet corrosion research has largely remained confined to two-dimensional flat plates, leaving the spatial-geometric effects on three-dimensional sections poorly quantified. This study addresses that gap through neutral salt spray (NSS) corrosion experiments on H-shaped steel specimens positioned at 0°, 45°, and 90° over corrosion cycles extending to 60 days, coupled with a three-dimensional cellular automata (3D-CA) model of the corrosion evolution. The spatial placement angle exerts a decisive influence on corrosion distribution. At 0° and 45°, the upper flange corrodes more severely than the web, while the lower flange remains least affected; the 45° specimen, however, exhibits accelerated attack because its inclined geometry prevents formation of a protective NaCl electrolyte film on the flanges. At 60 days, the 45° specimen's F1 surface shows average rust layer thickness and average pit depth exceeding those of the 0° specimen by 45.79% and 54.78%, respectively. At 90°, the W1 surface is most severely corroded, followed by the flanges, with W2 least affected. The 3D-CA model reproduces the time-dependent corrosion morphology, yielding pit depth distributions consistent with a Weibull function and agreeing with experimental pit morphology and depth within 5% error. The model is validated as a reliable predictor of spatially heterogeneous corrosion evolution in H-shaped steel, though it currently omits coupled stress and external loading effects.
1. Introduction
Structural steel corrosion research has historically relied on two-dimensional flat plate specimens, a simplification that fails to capture the spatially heterogeneous attack observed on real three-dimensional sections. H-shaped steel components, ubiquitous in modern steel construction, present a complex geometry in which flanges and web create distinct micro-environments for moisture retention, oxygen diffusion, and electrolyte accumulation. The resulting non-uniform corrosion patterns cannot be predicted from flat-plate data, yet systematic experimental and numerical studies on how spatial orientation governs corrosion evolution across individual H-section surfaces remain scarce. This knowledge gap leaves engineers without validated tools for allocating inspection resources or estimating remaining life in corrosion-prone H-shaped members.
This study confronts that bottleneck directly. Neutral salt spray experiments were conducted on H-shaped steel specimens positioned at 0°, 45°, and 90° over corrosion cycles up to 60 days, generating surface-resolved corrosion rate, rust layer thickness, and pit depth data. A three-dimensional cellular automata model was then constructed to simulate the dynamic corrosion process, incorporating the oxygen and chloride mechanisms operating under the electrolyte film. The experimental matrix specifically isolates spatial angle as the controlling variable, while the 3D-CA framework provides a predictive capability that flat-plate models cannot offer. Validation against measured pit morphology and depth distributions establishes the model's quantitative reliability and defines the conditions under which it can be applied.
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LIU Zhe, GU Wenxu, BAN Huiyong, ZHOU Xuejun, WEI Ruida (2026). Test and Simulation Analysis on the Corrosion Evolution over Time of H-shaped Steel Components. Surface Technology (表面技术). https://doi.org/10.16490/j.cnki.issn.1001-3660.2026.12.004
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Frequently Asked Questions
What is the dominant failure mechanism driving the accelerated corrosion observed at the 45° orientation, and how does it differ from the 0° and 90° cases?
At 45°, the inclined geometry prevents NaCl electrolyte from forming a stable protective film on the flanges, so the surface remains alternately wetted and dried rather than continuously covered. This intermittent wetting accelerates oxygen reduction and chloride attack, producing average rust layer thickness and pit depth on the F1 surface that exceed the 0° specimen by 45.79% and 54.78%, respectively, after 60 days. At 0°, the horizontal upper flange retains a more uniform electrolyte layer, moderating attack; at 90°, gravity drains the web faces differently, making W1 the most corroded surface and W2 the least.
The 3D-CA model reports pit depth error within 5%—what is the experimental baseline for that figure, and does it hold across all three spatial orientations?
The 5% error bound is established by comparing simulated pit morphology and depth distributions against measured NSS corrosion data after the full 60-day cycle. Simulated pit depths follow a Weibull distribution, matching the spatial non-uniformity and randomness seen in the experiments. The validation covers the 0°, 45°, and 90° specimens, with the closest agreement on surfaces where the electrolyte film behavior is well captured by the oxygen and chloride transport rules. Surfaces subject to more complex film dynamics, such as the 45° flanges, represent the upper end of the error range.
What are the scalability bottlenecks in applying this 3D-CA model to full-scale H-section members or large structural assemblies?
The current model operates at the coupon scale and does not incorporate coupled stress states or external loading, which are unavoidable in service. Extending it to full-scale members requires multi-scale coupling from microstructural pit initiation to macroscopic property degradation, plus calibration against field exposure data rather than accelerated NSS results. Computational cost scales with the number of cells needed to resolve pit geometry across meter-scale components, so mesh coarsening strategies and parallelization will be necessary before plant-level or bridge-level deployment.
How should inspection and maintenance protocols for H-shaped steel structures be revised based on the orientation-dependent corrosion hierarchy reported here?
The data show that a single corrosion allowance derived from flat-plate tests will misallocate inspection effort. For horizontal or near-horizontal members, the upper flange and web demand priority; for inclined members near 45°, the flanges—especially F1—require the shortest inspection interval because of the 45.79% and 54.78% penalties in rust thickness and pit depth relative to 0°. For vertical members at 90°, W1 becomes the critical surface, with flanges secondary and W2 least affected. Inspection schedules should therefore be indexed to both member orientation and surface position rather than treated as uniform.
What is the cost or performance trade-off between the 3D-CA simulation approach and conventional empirical corrosion models for engineering practice?
Conventional empirical models are inexpensive but cannot resolve surface-to-surface variation within a single H-section, which the present experiments show can exceed 50% in pit depth between orientations. The 3D-CA model requires computational resources and calibration data but delivers spatially resolved pit depth distributions with under 5% error, enabling targeted inspection and more accurate remaining-life estimates. The trade-off is justified where corrosion-driven failure carries high consequence or where inspection access is costly; for low-risk, uniformly exposed members, empirical allowances may remain sufficient.
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