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Record W4200617114 · doi:10.18280/ijsse.110609

Vinyl Acetate Emission Rates and Explosions in Tank Farms in Dilovasi and Yumurtalik, Turkey: A Case Study

2021· article· en· W4200617114 on OpenAlexvenueno aff
Halil Dertli, Didem Saloğlu

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsFlammable liquidVinyl acetateAlohaVinyl chlorideEnvironmental scienceStorage tankOrange (colour)Waste managementEnvironmental engineeringChemistryEngineeringTelecommunicationsOrganic chemistry

Abstract

fetched live from OpenAlex

The emission estimations for vinyl acetate from storage tanks located in Dilovasi and Yumurtalik, Turkey, were completed by using the US EPA standard regulatory storage tanks emission model (TANKS 4.9b). Total annual emission was determined to be 7,603.15 kg/year for Yumurtalik and 6,057.06 kg/year for Dilovasi. In addition, ALOHA software was used in order to define emergency responses required in the case of vinyl acetate leakage based on different scenarios. According to ALOHA program modelling results, the threat regions occurred were 113 and 236 m for the red threat region, 299 and 663 m for the orange threat region, and 790 m and 2.0 km for the yellow threat region for vinyl acetate toxic vapour in Dilovasi and Yumurtalik, respectively. The threat regions determined were 10 and 15 m for the red threat region, 9.14 m for orange threat region, and 20 and 49 m for the yellow threat region for modelling of flammable area for the vapour cloud of vinyl acetate in Dilovasi and Yumurtalik, respectively. The amount of thermal radiation was determined to be 10 kW/m2 at a distance of 9.96 m from the tanks in both Dilovasi and Yumurtalik during a jet fire.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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 designObservational
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

Citations3
Published2021
Admission routes1
Has abstractyes

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