Galvanic Corrosion Risk Assessment of Bolt Materials in Contact with ASTM a1010 Steel Bridges
Bibliographic record
Abstract
Abstract This study has evaluated the galvanic coupling corrosion risk between connection bolt materials with ASTM A1010 structural steel, which has recently emerged for the construction of more corrosion-resistant bridges than weathering steel bridges. Use of A1010 steels containing 10.5% Cr is intended to extend the service life of steel bridges without frequent maintenance requirements caused by corrosion, particularly in regions under severe chloride exposures such as due to heavy use of de-icing salts and in marine environments. The greater corrosion resistance of A1010 steel with a more positive corrosion potential does, however, impose a risk of galvanic corrosion with the connection bolts in direct electrical contact. Here, the galvanic corrosion between A1010 steel and galvanized ASTM A325 Type I bolt was compared to that between weathering steel and galvanized ASTM A325 Type I bolt, as well as that between A1010 steel and ASTM A320 B8 class 2 and A193 B6 stainless steel bolts. A comprehensive experimental investigation measured galvanic coupling current and potential for samples in cells of aerated salt solution, and the galvanic corrosion risk ranking was validated by visual examinations of bolted steel plates exposed to a salt spray testing chamber. The galvanic corrosion risk of using B8 class 2 bolts with A1010 steel was found to be much lower than using galvanized A325 bolts, but B6 bolt material itself experienced severe crevice and pitting corrosion in both simulated salt solution and salt spray testing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".