Concrete Bridge Deck Deterioration Assessment Using Ground Penetrating Radar (GPR)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Ground penetrating radar (GPR) has become an effective means for assessing deterioration in concrete bridge decks. While success has been demonstrated, the method is still not adopted widely. Constant technical development is making such high speed GPR mapping more affordable with systems more widely available and easier to deploy. The American Society for Testing and Materials (ASTM) has a standard procedure for performing bridge deck deterioration using GPR. The current standard, initially written for air-launched GPR devices and then modified to include ground-coupled GPRs, has many simplifying assumptions that could lead to fallacious evaluations. Both field experience and numerical simulations indicate that ground-coupled GPR systems are preferable to air-launched GPRs in this application, delivering larger signal-to-noise and higher spatial resolution data, which enhance extraction of both electromagnetic wave velocity and attenuation. We describe advances in analysis and interpretation that go beyond the current ASTM approach which ignores the impact of depth and other variables. We demonstrate these advances using a high speed, ground-coupled GPR system with examples of deck deterioration mapping. We describe the workflow for using GPR to evaluate the deterioration of concrete bridge decks, highlight the basic interpretation assumptions, demonstrate successful applications and discuss limitations with the methodology.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it