Data · dataset · 2026
Structure Generation and Seepage Performance Analysis of Porous Oil Containing Media with Variable Porosity Gradient Distribution
Listed in ScienceDB
To elucidate the influence of different porosity distributions on the seepage performance of oil-bearing media, a stochastic growth method of variable-gradient porous structures, governed by regulation functions, was developed.
Description
This approach enabled the generation of porous architectures with porosity varying along the height direction, including linear gradient structures (positive and negative gradients) and parabolic gradient structures (convex and concave types).
The lattice Boltzmann method (LBM) was employed to analyze the seepage behavior of lubricating oil within the porous medium. The results demonstrate that, under identical porosity conditions, the heterogeneity of pore distribution exerts a pronounced effect on fluid transport. Specifically, the average seepage velocities in both positive and negative linear gradient structures were lower than those in homogeneous porous structures, while the velocity in the negative gradient configuration was significantly higher than in its positive counterpart.
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Furthermore, an increased amplitude of linear porosity variation was found to deteriorate seepage performance. In contrast, parabolic gradient distributions exhibited enhanced permeability, with convex and concave structures achieving average seepage velocity improvements of 44.6% and 61.7%, respectively, compared with the homogeneous case. Notably, the convex gradient structure exhibited a distinctive "center-accelerated and edge-retarded" seepage behavior, conferring a marked advantage in sustaining lubrication performance.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.0124w ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Experimental methods in fluid flow, heat and mass transfer 76%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.0124w | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:401205 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (76%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |