Localized Corrosion Management for Thermally Insulated Systems via Insulation Standoffs and Low Point Drains
Bibliographic record
Abstract
Abstract CUI (corrosion under insulation) is a major damage mechanism affecting the integrity of process equipment, piping, and pipelines. CUI is known to create localized corrosion and pitting under thermal insulations which trigger non-linear corrosion rates and end up in unanticipated leaks in industrial assets. Reportedly, detection and management of CUI-driven damages constitute 10% of the maintenance budget in a typical refinery. This study simulates the CUI behavior of carbon steel under fibrous stone wool insulation using four testing conditions namely Isothermal wet, isothermal wet-dry, cyclic wet, and cyclic wet-dry. The weight loss of coupons under each test condition was converted into corrosion rate followed by characterization of damage modes namely pitting, uniform corrosion via microscope, and surface topography. It also compares the corrosion behaviors in closed-contacting insulation to those produced under contact-free insulation with low-point drains under similar testing conditions. Unlike closed-contacting insulations, coupons under contact-free insulation with low-point drainage resulted in uniform corrosion, insignificant pitting, and reduced corrosion rates under all testing conditions.
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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 | 0.000 | 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) | 0.001 | 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 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".