Unveiling microstructural heterogeneity, mechanical properties, and microbiologically induced selective corrosion in Q355 welded joints
Source abstract
Abstract
This study systematically investigates the microstructure, mechanical performance, and microbiologically induced selective corrosion mechanisms of Q355 welded joints extracted from an offshore wind turbine tower. The results show that rapid cooling during welding significantly refines the grains in the welding zone (WZ), leading to the formation of high-angle grain boundaries and distinct crystallographic textures. In contrast, under welding heat input, the base metal (BM), initially consisting of polygonal ferrite and granular bainite, transforms into a microstructure dominated by upper bainite and continuously distributed carbides, thereby forming the heat-affected zone (HAZ). This region exhibits the highest density of low-angle grain boundaries and dislocations, rendering it the weakest zone in both mechanical and microbial corrosion tests. Mechanical testing shows that the yield strength of the welded region increases to 492.8 MPa compared with the BM, while elongation decreases to 11.1%. Microbiologically influenced corrosion (MIC) experiments further reveal a pronounced tendency for selective corrosion in the presence of Pseudomonas aeruginosa . Specifically, the corrosion current density in the HAZ increases to 11.6 μA·cm -2 , accompanied by the greatest levels of biofilm accumulation and pit density. This tendency is further exacerbated by galvanic coupling. This study provides mechanistic insights into how microstructural heterogeneity governs both the intrinsic mechanical properties and the selective degradation of Q355 welded joints under marine service conditions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Corrosion Behavior and Inhibition · Hydrogen embrittlement and corrosion behaviors in metals · Structural Integrity and Reliability Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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