Corrosion Scale and Moisture Assessments – an Improvement to On-Stream Inspections for CUI Management
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 Corrosion under insulation refers to localized corrosion under thermal insulations which has resulted in failure incidents in the hydrocarbons industry. The non-destructive examination (NDE) inspections for in-service assets (pipes, equipment) via stripping-off insulations are generally limited to a few feet (or meters) as the removal of insulations from larger sections is limited by the safety issues and required heat conservations in the assets. For these reasons, major CUI inspections are generally performed only during outage conditions, as it permits access and inspections for larger areas. On the other hand, the ambient temperatures (due to the out-of-service conditions) which also results in the moisture buildup on the insulated metals (via condensation), change the chemical composition of the corrosion scale and in turn, the kinetics and mode of the corrosion damage. Therefore, traditional NDEs conducted on out-of-service assets do not mimic the periodical in-service CUI damage. Moreover, there have been many events where insulated assets failed while in service as the metal loss rate from the localized CUI damage exceeded the future corrosion allowance. This study proposes an improved methodology for in-service CUI inspections via accounting for the chemical nature of corrosion products, insulation materials, moisture assessments, etc. to better predict the CUI damage.
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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