Evaluation of Two Automated Methods for Air-Void Analysis of Hardened Concrete
Bibliographic record
Abstract
Abstract Air-void analysis of hardened concrete is typically performed according to ASTM C457–09 [“Standard Test Method for Microscopical Determination of Parameters of Air-Void System in Hardened Concrete,“ Annual Book of ASTM Standards, Vol. 4.2, ASTM International, West Conshohocken, PA], which can be tedious to perform and is operator subjective. Several alternative automated methods have been proposed, two of which are the Rapid Air 457 and the scanner method developed at Michigan Technological University. In each of these methods, images are collected from contrast enhanced surfaces of polished concrete, and image analysis is performed to calculate air-void system parameters. In this research, 22 concrete samples were examined using these two methods, the air-void system parameters were compared to those obtained from the ASTM C457 standard, and the precision of the results was compared to the recommendations of ASTM standard. It was concluded that the total air content and the spacing factor of the air voids measured by Rapid Air 457 and the scanner method were comparable to the air content and the spacing factor measured according to the standard manual method. Considering the fact that the automated image systems could detect air voids smaller in diameter than those typically seen by an operator, it was found that if these small air voids are counted, calculated spacing factors are smaller than those calculated by the manual method. If small diameter air voids are removed from the analysis, then spacing factors agree fairly well with those calculated by ASTM C457 from stereo-optical microscopy.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".