ArticleACS omega2025
Numerical Study of Turbulent Wind Flow and Hydrocarbon Dispersion in Crude Oil Tank Farms.
Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a critical link connecting upstream and downstream sectors in the petrochemical industry, crude oil storage tank farms serve as vital hubs for production, transfer, and import/export operations, where safety management presents unique complexities. However, current safety regulations have failed to keep pace with the rapid development of the petrochemical sector, leading to frequent oil-gas leakage incidents. This study investigates the stress states of hydrocarbon components (both near-leakage sources and far-field) and their mixing characteristics with air under complex turbulent flow conditions. We establish a numerical model and solution algorithm capable of describing cross-scale oil-gas dispersion and cloud evolution dynamics. The model is applicable to (1)-High-speed regions near leakage sources (<300 m/s, without shockwave structures); (2)-Far-field environments where atmospheric turbulence dominates hydrogen dispersion concentration fields. Through numerical simulations studies conducted at an actual crude oil, we systematically analyze the "leakage-mixing, cloud formation, dispersion-migration, and flow-dilution" processes under various scenarios. The work quantifies the spreading range and concentration distribution of hydrocarbon clouds at different stages, providing theoretical guidance for quantitative risk assessment of oil-gas leaks in storage areas and Emergency response design.
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Registered trials
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