Evaluation of Corrosion Resistance of Steel Dowels Used for Concrete Pavements
Bibliographic record
Abstract
In concrete pavements, steel dowels are exposed to a particularly aggressive environment that leads to depassivation and greatly reduces the corrosion initiation stage. Aggressive agents such as chlorides and CO2 have easy access to the dowels through pavement joints and, consequently, the corrosion performance of the system depends largely on the properties of the steel dowel being used. This study investigates the corrosion performance of several types of steel dowels embedded in concrete and subjected to accelerated corrosion by exposure to 3.5% NaCl solution for 18months. Seven types of dowels were tested: bare carbon steel, stainless steel clad, grout-filled hollow stainless steel, microcomposite steel, carbon steel coated with bendable epoxy, and carbon steel coated with nonbendable epoxies. Half-cell potential, polarization resistance, visual inspections, and microscopic investigations by scanning electron microscopy were carried out to evaluate their corrosion performance. Results show that microcomposite steel dowels exhibit greater resistance to corrosion propagation than carbon steel dowels, but lesser than stainless clad and stainless hollow bars. In epoxy-coated bars, corrosion occurred at a few localized defective areas, generally at holidays and edges of bar ends. No significant difference was observed between nonbendable and bendable epoxy-coated dowels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".