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Record W4411049942 · doi:10.1016/j.ptlrs.2025.05.006

Oil flow impact characteristics of internal floating roof tanks during floating roof landing and oil receiving processes

2025· article· en· W4411049942 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

VenuePetroleum Research · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsPetro-Canada
FundersScience and Technology Major Project of GuangxiNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of China
KeywordsRoofEnvironmental sciencePetroleum engineeringFlow (mathematics)GeologyMarine engineeringEngineeringCivil engineeringMechanics

Abstract

fetched live from OpenAlex

To maintain the integrity of internal floating roof tanks, curb environmental pollution and guarantee the safety of tank farms, it is important to determine the oil flow features that impact the floating roof during the oil receiving process, especially when the floating roof falls to the bottom of the tank. In this study, the finite volume, volume of fluid (VOF), and realizable k-ε turbulence models and the pressure implicit with splitting of operators (PISO) algorithm were adopted to establish a three-dimensional physical model of an internal floating roof tank and simulate the oil receiving process. A pressure test platform was then set up to validate the model’s viability. The flow field characteristics and influencing properties of the impact of the liquid against the floating roof under different oil inlet velocities, initial liquid levels, medium densities, and tank diameters were analyzed and compared. The results showed that increasing the oil inlet velocity and medium density led to the maximum pressure and the impact force at different moments of the liquid against the floating roof also increasing. An increase in the oil inlet velocity, led to greater turbulence on the opposite the inlet, and higher pressure at the edge of the floating roof in the upper area opposite the inlet. At an oil inlet velocity of 4.0 m/s, the maximum pressure was 135.5 kPa and the maximum impact force peak was 13.967 MN. The initial liquid level increase had little influence on the liquid’s impact on the floating roof, and the high pressure zone was at the edge of the floating roof opposite the inlet. When the initial level was 0.5 m, the maximum pressure was 135.81 kPa and the maximum impact force peak was 14.021 MN. As the density of the medium increased, the greater the turbulence on the inlet relative side and the higher pressure at the edge of the floating roof in the upper area of the inlet relative side. When diesel was the medium, the maximum pressure was 154.9 kPa and the maximum impact force peak was 15.999 MN. As the diameter of the tank increased, the maximum pressure of the floating roof impacted by the liquid reduced, but the impact force increased. The slower the turbulence on the inlet relative side, the greater the maximum pressure zone of the floating roof. When the tank volume was 1000 m 3 , the maximum pressure was 135.5 kPa. When the tank volume was 10000 m 3 , the maximum impact force peak was 81.978 MN. Considering the above, a low velocity, a low-density light oil, and an internal floating roof tank with a small diameter are recommended for engineering operations that involve receiving oil. Further increased safety precautions at the edge of the floating roof opposite the inlet are needed. In sum, the findings of the study offer theoretical justifications and a technical reference for optimizing the structural design of floating roofs and the oil receiving and delivering process.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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