MétaCan
Menu
Back to cohort
Record W4312567502 · doi:10.1115/pvp2022-84863

Case History of Hydrotreater Prefeed Heater Fire Recovery

2022· article· en· W4312567502 on OpenAlexaff
Jorge Penso, Neil Park, Mitul Dalal, Alexandra Hosack

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsTube (container)Materials scienceHydrogenConvectionRadiant heatNuclear engineeringComposite materialEngineeringChemistryMeteorology

Abstract

fetched live from OpenAlex

Abstract A prefeed heater in a hydrotreater unit experienced a fire while being prepared for shutdown during a turnaround. The prefeed hydrotreater heater was a mixed operation heater that typically operated in mixed mode with hydrogen and hydrocarbon bitumen, but at the time of the incident was operating in hydrogen only mode in order to hot hydrogen strip the hydrotreater. The heater had been in operation since 2011 and had a design fluid temperature of 425 °C (797 °F), a tube metal temperature of 570 °C (1058 °F) and design pressure of 16,800 kPag (2437 Psig). The normal operating pressure was 15,000 kPag (2176 Psig). The radiant and convection tubes were fabricated from Type 316Nb stainless steel (UNS31640). There was a tube rupture in the radiant section that caused the fire and the subsequent failure investigation established that the temperature in the radiant section at the rupture location had reached in excess of 850 °C (1562 °F) for over a 15-minute period prior to rupturing. The following paper outlines the failure analysis and root causes which caused the incident, while detailing the recovery and construction of the heater, including the fitness-for-service methods and inspections conducted. The heater was partially rebuilt with the convection section tube material being recovered and the radiant section being rebuilt in a different metallurgy.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.182
Teacher spread0.166 · 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 designCase report
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicCombustion and Detonation ProcessesFrench-language works237,207