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Record W2902755445 · doi:10.1115/pvp2018-84545

Repair and FFS of Vacuum Column for Corrosion Under Insulation

2018· article· en· W2902755445 on OpenAlexaff
Yeswanth Kumar Adusumilli, Siva Kumar Chiluvuri, Ayman Cheta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsWeldingMaterials scienceFillet weldFillet (mechanics)Composite materialCorrosionUltrasonic testingMetallurgyStructural engineeringUltrasonic sensorEngineeringAcoustics

Abstract

fetched live from OpenAlex

One of the vacuum column made of Carbon steel (SA 285 Gr. C) was found with severe corrosion under insulation during turnaround inspection. The equipment was in service for the past 46 years. The corrosion was around the full circumference of the column at a location immediately above the stiffener ring. The wall loss was extensive, which mandated a welded full circumferential patch to encapsulate the corroded region. A full circumferential lap patch with reinforcement plug welds was designed as per ASME PCC-2 [2], fabricated and installed at site. During the dye penetrant examination of the patch plate welds, fine cracks were noted at the toe of the fillet welds. A subsequent PAUT (Phased Array Ultrasonic Testing) of patch plate welds, showed that the cracks were in column shell (base material) surface initiating from toe of the fillet weld of the patch and beneath the fillet weld. The cracks found in first few sections of welds were ground and re-welded with appropriate pre-heating and post-heating. However, some cracks were still observed in base material, although with reduced magnitude compared to previous welding. Despite proper controls in place during the welding, the challenge was, some minor cracks were re-occurring at the base material surface below fillet welds. A multi discipline review was carried out to understand the potential root cause for the cracks, detailed assessment of risks and impact due to the cracks. A risk based approach was followed, in evaluating cracks for acceptance based on API 579-1/ASME FFS-1 [1], for continued service of the column and to minimise the extension of turn around duration. Later, a long-term plan was made to replace the equipment.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.026
GPT teacher head0.296
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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