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Record W3167347975 · doi:10.5006/c2020-15234

Passive Fire Protection Considerations for Oil Sands Applications

2020· article· en· W3167347975 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCoal Combustion and Slurry Processing
Canadian institutionsSuncor Energy (Canada)
Fundersnot available
KeywordsOil sandsPetroleum engineeringEnvironmental sciencePetroleumFire protectionWaste managementForensic engineeringGeologyMaterials scienceEngineeringCivil engineeringComposite materialAsphalt

Abstract

fetched live from OpenAlex

Abstract Oil sands projects have unique features due to process conditions and environmental factors. Process safety risks such as fire hazards are typically mitigated through application of Passive Fire Protection (PFP). Cementitious and intumescent PFP types are commonly used to protect plant structures. Cladding type or flexible jackets are more common for fire protection of piping systems and safety critical components including equipment, valves and instrumentation systems. Due to weather conditions, application of PFP products at plant site or modular construction requiring transportation over long distances may pose risks for major projects. This study aims to share lessons learnt and recommendations for selection of PFP types for oil sands projects and facilities with similar environmental and process conditions. Critical considerations for selection of PFP type in the oil sands fields are discussed in this study with respect to abrasion resistance, short- and long- term integrity, and corrosion under insulation risks. This study provides case studies and recommendations for PFP selection and application at cold regions where the facility has high momentum jet fire risks similar to those at oil sands facilities. Also, methods to optimize PFP application are discussed so that required coating quantities can be minimized and potential integrity issues can be mitigated. This approach is expected to be beneficial for reducing coating related Capital Expenses (CAPEX) and Operational Expenses (OPEX) at oil sands and other process plants where there are fire risks.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

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

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 head0.041
GPT teacher head0.237
Teacher spread0.196 · 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

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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