Comparison of Destructive Methods to Appraise the Mechanical Integrity of a Concrete Surface
Bibliographic record
Abstract
Depending on the technique being used, the concrete removal operation prior to repair can be harmful to the residual concrete skin left on the structure.Whenever a tight bond between the repair and the old concrete is required, the soundness of the prepared surface should thus be assessed.Although this is widely recognized, there is no standard method intended to characterize the integrity of a concrete substrate after concrete removal.This paper presents the results of an investigation intended to assess and compare quantitatively different test methods, namely the Schmidt rebound hammer, the Capo and Accelerated cohesion pullout tests, and the pull off test, to evaluate superficial mechanical integrity of a substrate after concrete removal operations.Although it does not yield a precise evaluation of compressive strength, the Schmidt rebound hammer test is recognized as a useful tool for performing quick surveys to assess concrete uniformity.The pull off test is very well correlated with the splitting-tensile test, but it is not suited for vertical and overhead surfaces.The Capo pullout test has limited interest for surface preparation, as it is applicable to flat surfaces only.Conversely, the Accelerated cohesion test showed interesting potential as a simple tool for assessing the mechanical integrity of a concrete surface prior to repair for any type of concrete surface.More work is required to refine the procedures and develop statistically based acceptance criteria.Nevertheless, it appears from the results generated in this study that the combination Schmidt hammer / pull off tests could fulfill the needs for the evaluation of horizontal surfaces after concrete removal, while the combination Schmidt hammer / Accelerated cohesion tests could be used effectively on any surface, irrespective of its orientation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".