4D evolutions of cracks, voids, and corrosion products in reinforced concrete materials
Bibliographic record
Abstract
This research paper presents a comprehensive investigation into the corrosion process in reinforced concrete structures using advanced analytical techniques, namely non-destructive X-ray computed tomography (CT) imaging, scanning electron microscopy (SEM) images, energy dispersive x-ray spectrometry (EDS), and Raman spectroscopy. The CT image analysis allowed for the identification and quantification of pore structures, crack propagation, and corrosion progression at different stages of corrosion. CT scanning and data analysis offer valuable 4D (3D spatial + time) insights into corrosion in reinforced concrete, revealing changes in pore sizes, with smaller pores increasing and larger pores decreasing as corrosion progresses. Our investigation reveals dynamic changes in reinforced concrete pores during the accelerated corrosion test leading to new pore formation and cracking. The research identifies two distinct types of cracks: one filled with corrosion products and the other, zipper-like cracks, resulting from the connection of deformed pores without corrosion products. The SEM images and EDS analysis confirmed the absence of corrosion products within these unique zipper cracks, suggesting a different mechanism of crack formation compared to the first type of cracks. The results revealed two distinct categories of corrosion products: iron oxides and iron hydroxides, with their distribution correlated to the duration of accelerated corrosion testing. The integration and verification of results from X-ray CT imaging and Raman spectroscopy established a comprehensive understanding of corrosion-induced damage in the reinforced concrete specimen, shedding light on complex interactions among different corrosion products during the corrosion process. These findings offer crucial insights for better understanding of the corrosion process in reinforced concrete paving the way for future development of effective treatments and strategies to mitigate corrosion impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".