Fluid dynamics simulation on water lubricating performance of micro-/nano-textured surfaces considering roughness structures Article Swipe
Jianfa Gu
,
Ting Zheng
,
Mingjin Guo
,
Dongsheng Xia
,
Huichen Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7498/aps.73.20240333
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7498/aps.73.20240333
With the development of surface precision machining technology and extensive studies on lubrication and friction reduction, the use of surface texture to reduce friction has attracted widespread attention, but few studies have considered the influence of surface roughness on lubrication characteristics. By employing the computational fluid dynamics (CFD) simulation method, the lubrication models with rectangular textures and the introduction of rough asperity structures at the same time are established. The effects of the corresponding structure parameters on the lubrication performance of textured and roughed surfaces are studied under water lubrication conditions. Our results suggest that the adjustment of geometric parameters on the micro-/nano-structured surfaces can influence the load-bearing capacity of the water lubrication film, thus affecting the hydrodynamic lubrication performance on the surface. In addition, the generation of vortex in the micro-textures can bring changes in vorticity, which causes energy dissipation and affects frictional forces. In the lubrication model with rectangular textures, optimal hydrodynamic lubrication performance is obtained under the appropriate depth ratio H = 0.6. Meanwhile, the corresponding lubrication performance can be enhanced by increasing the width ratio (W) of surface texture. After introducing random asperity structures on the micro-textured surface with a standard deviation δ = 0.5, the bearing capacity is increased by 44%, and the friction coefficient is reduced by 30.9%. Moreover, the introduction of half-sine rough asperity structures can only result in relatively minor differences in the lubrication performance, i.e. the changes of bearing capacity and friction coefficient are less than 10%. However, the introduction of compound hierarchical structure consisting of random asperity structures and half-sine rough asperity structures can result in an increase in the corresponding bearing capacity by 42% and a reduction in the friction coefficient by 31.1%, which implies a significant enhancement in the hydrodynamic lubrication performance.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7498/aps.73.20240333
- https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.73.20240333.pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4395055681
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- OpenAlex ID
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https://openalex.org/W4395055681Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7498/aps.73.20240333Digital Object Identifier
- Title
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Fluid dynamics simulation on water lubricating performance of micro-/nano-textured surfaces considering roughness structuresWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
Jianfa Gu, Ting Zheng, Mingjin Guo, Dongsheng Xia, Huichen ZhangList of authors in order
- Landing page
-
https://doi.org/10.7498/aps.73.20240333Publisher landing page
- PDF URL
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https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.73.20240333.pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://wulixb.iphy.ac.cn/pdf-content/10.7498/aps.73.20240333.pdfDirect OA link when available
- Concepts
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Nano-, Materials science, Surface finish, Surface roughness, Nanotechnology, Dynamics (music), Composite material, Physics, AcousticsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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40Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.increased | 203 |
| abstract_inverted_index.influence | 34, 105 |
| abstract_inverted_index.machining | 6 |
| abstract_inverted_index.precision | 5 |
| abstract_inverted_index.reduction | 277 |
| abstract_inverted_index.roughness | 37 |
| abstract_inverted_index.structure | 74, 252 |
| abstract_inverted_index.textures, | 151 |
| abstract_inverted_index.Meanwhile, | 166 |
| abstract_inverted_index.adjustment | 96 |
| abstract_inverted_index.attention, | 27 |
| abstract_inverted_index.considered | 32 |
| abstract_inverted_index.consisting | 253 |
| abstract_inverted_index.frictional | 143 |
| abstract_inverted_index.generation | 126 |
| abstract_inverted_index.increasing | 175 |
| abstract_inverted_index.parameters | 75, 99 |
| abstract_inverted_index.reduction, | 15 |
| abstract_inverted_index.relatively | 226 |
| abstract_inverted_index.simulation | 48 |
| abstract_inverted_index.structures | 62, 187, 221, 257, 262 |
| abstract_inverted_index.technology | 7 |
| abstract_inverted_index.vorticity, | 136 |
| abstract_inverted_index.widespread | 26 |
| abstract_inverted_index.appropriate | 160 |
| abstract_inverted_index.coefficient | 209, 241, 281 |
| abstract_inverted_index.conditions. | 90 |
| abstract_inverted_index.development | 2 |
| abstract_inverted_index.differences | 228 |
| abstract_inverted_index.dissipation | 140 |
| abstract_inverted_index.enhancement | 288 |
| abstract_inverted_index.introducing | 184 |
| abstract_inverted_index.lubrication | 12, 39, 51, 78, 89, 112, 118, 147, 154, 169, 231, 292 |
| abstract_inverted_index.performance | 79, 119, 155, 170 |
| abstract_inverted_index.rectangular | 54, 150 |
| abstract_inverted_index.significant | 287 |
| abstract_inverted_index.established. | 68 |
| abstract_inverted_index.hierarchical | 251 |
| abstract_inverted_index.hydrodynamic | 117, 153, 291 |
| abstract_inverted_index.introduction | 58, 216, 248 |
| abstract_inverted_index.load-bearing | 107 |
| abstract_inverted_index.performance, | 232 |
| abstract_inverted_index.performance. | 293 |
| abstract_inverted_index.computational | 44 |
| abstract_inverted_index.corresponding | 73, 168, 270 |
| abstract_inverted_index.micro-textured | 190 |
| abstract_inverted_index.micro-textures | 131 |
| abstract_inverted_index.characteristics. | 40 |
| abstract_inverted_index.<i>H</i> | 163 |
| abstract_inverted_index.<i>δ</i> | 196 |
| abstract_inverted_index.(<i>W</i>) | 179 |
| abstract_inverted_index.micro-/nano-structured | 102 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/6 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Clean water and sanitation |
| citation_normalized_percentile.value | 0.50024586 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |