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Record W3177040909 · doi:10.1016/j.jlp.2021.104569

Review of hydrogen safety during storage, transmission, and applications processes

2021· article· en· W3177040909 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

VenueJournal of Loss Prevention in the Process Industries · 2021
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsProcess safetyRisk analysis (engineering)Process (computing)Hydrogen storageHydrogenRisk assessmentComputer scienceEngineeringTransmission (telecommunications)Hydrogen technologiesBiochemical engineeringReliability engineeringEnvironmental scienceHydrogen fuelWork in processFuel cellsBusinessOperations managementHydrogen economyChemistryTelecommunicationsComputer security

Abstract

fetched live from OpenAlex

Hydrogen is considered an excellent clean fuel with potential applications in several fields. There are serious safety concerns associated with the hydrogen process. These concerns need to be thoroughly understood and addressed to ensure its safe operation. To better understand the safety challenges of hydrogen use, application, and process, it is essential to undertake a detailed risk analysis. This can be achieved by performing detailed consequence modellings and assessing risk using the computational fluid dynamics (CFD) approach. This study comprehensively reviews and analyses safety challenges related to hydrogen, focusing on hydrogen storage, transmission, and application processes. Range of release and dispersion scenarios are investigated to analyse associated hazards. Approaches to quantitative risk assessment are also briefly discussed.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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