Quebec Bridge Inspection Using Common Nondestructive and Destructive Testing Techniques
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
Various nondestructive testing (NDT) techniques are available to evaluate the condition of existing concrete structures. These NDT techniques can help to determine in-situ load carrying capabilities and in turn be used to help develop a cost effective rehabilitation solution. In this project, the four pier caps of Denver Colorado' Quebec Street Bridge over Air Lawn Road were inspected using several different NDT techniques. These tests included: carpenter hammer sounding, Schmidt hammer, and ultrasonic pulse velocity (UPV) testing including tomography. In addition visual testing was used to identify crack patterns and spalling conditions. Contour plotting of the NDT data was completed on individual and combined NDT techniques to better determine the condition of the piers. Equal weighted percentages were assumed in combining the hammer sounding, Schmidt, and direct ultrasonic transmission data. Although hammer sounding and Schmidt rebound techniques were used to determine the condition of the exterior layers of the piers, ultrasound and tomography were used to determine the condition of the interior. Various tomographic slices were completed between adjacent sides and from face to face. After the NDT tests were completed, the data were analyzed, interpreted and recommendations were given to further destructively examine local areas of the piers. Destructive tests included compressive strength, chloride, and petrographic testing. The specific detail of all testing methodologies used in this study will be discussed further along with the specific results for the northwest pier cap.
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.
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