PR-393-205100-R01 IRIS X-Ray CT Qualification for Flexible Pipe Inspection (Phase 1)
Bibliographic record
Abstract
There are several techniques available to inspect single wall carbon steel pipelines including; Magnetic flux leakage (MFL), ultrasonic testing (UT), Electro-Magnetic Acoustic Transducer (EMAT), Phased Array, guide wave testing (GWT), etc. However, for more complex structures such as flexible pipelines the technology available to inspect them is far more limited. PRCI commissioned a program (SPIM 2-1) under the Subsea TC (2017-2020) to evaluate all known and suspected technologies that could be used to provide a detailed subsea inspection of a flexible riser. PRCI produced four samples of flexible pipe containing pre-manufactured cracks and corrosion defects which were located in; the outer armour layer, inner armour layer, pressure vault and carcass. The samples were used for blind testing of all identified inspection technologies. On conclusion of the SPIM 2-1 program, HR-XCT was identified as the technology showing the most promise and a follow-on program (SPIM 2-2) was commissioned to further explore the capabilities. This report will show the way in which high resolution image clarity and image manipulation was extracted from the HR-XCT system when used on the PRCI flexible pipe samples. The XCT results from SPIM 2-2 will be presented to show the initial setup of the experiment and 2D and 3D high resolution sectioned images from the testing. These images clearly identify and characterize 100% of the pre-manufactured defects introduced into the samples in all layers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.248 | 0.155 |
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".