Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method
The interaction of spherical solid particles with turbulent eddies in a 3-D turbulent channel flow with friction Reynolds number was studied. A generalized lattice Boltzmann equation (GLBE) was used for computation of instantaneous turbulent flow field for which large eddy simulation (LES) was emp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Isfahan University of Technology
2016-01-01
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| Series: | Journal of Applied Fluid Mechanics |
| Subjects: | |
| Online Access: | http://jafmonline.net/JournalArchive/download?file_ID=39830&issue_ID=228 |
| _version_ | 1811277236117962752 |
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| author | Mandana Samari Kermani Saeed Jafari Mazyar Salmanzadeh Mohamad Rahnama |
| author_facet | Mandana Samari Kermani Saeed Jafari Mazyar Salmanzadeh Mohamad Rahnama |
| author_sort | Mandana Samari Kermani |
| collection | DOAJ |
| description | The interaction of spherical solid particles with turbulent eddies in a 3-D turbulent channel flow with friction Reynolds number was studied. A generalized lattice Boltzmann equation (GLBE) was used for computation of instantaneous turbulent flow field for which large eddy simulation (LES) was employed. The sub-grid-scale (SGS) turbulence effects were simulated through a shear-improved Smagorinsky model (SISM), which can predict turbulent near wall region without any wall function. Statistical properties of particles behavior such as root mean square (RMS) velocities were studied as a function of dimensionless particle relaxation time ( ) by using a Lagrangian approach. Combination of SISM in GLBE with particle tracking analysis in turbulent channel flow is novelty of the present work. Both GLBE and SISM solve the flow field equations locally. This is an advantage of this method and makes it easy implementing. Comparison of the present results with previous available data indicated that SISM in GLBE is a reliable method for simulation of turbulent flows which is a key point to predict particles behavior correctly. |
| first_indexed | 2024-04-13T00:13:16Z |
| format | Article |
| id | doaj.art-173b002c4e29484fa55ec15d238417da |
| institution | Directory Open Access Journal |
| issn | 1735-3572 |
| language | English |
| last_indexed | 2024-04-13T00:13:16Z |
| publishDate | 2016-01-01 |
| publisher | Isfahan University of Technology |
| record_format | Article |
| series | Journal of Applied Fluid Mechanics |
| spelling | doaj.art-173b002c4e29484fa55ec15d238417da2022-12-22T03:11:02ZengIsfahan University of TechnologyJournal of Applied Fluid Mechanics1735-35722016-01-019313491357.Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann MethodMandana Samari Kermani0Saeed Jafari1Mazyar Salmanzadeh2Mohamad Rahnama3Shahid bahonar university of Kermanshahid bahonar university of kermanShahid bahonar university of KermanShahid bahonar university of KermanThe interaction of spherical solid particles with turbulent eddies in a 3-D turbulent channel flow with friction Reynolds number was studied. A generalized lattice Boltzmann equation (GLBE) was used for computation of instantaneous turbulent flow field for which large eddy simulation (LES) was employed. The sub-grid-scale (SGS) turbulence effects were simulated through a shear-improved Smagorinsky model (SISM), which can predict turbulent near wall region without any wall function. Statistical properties of particles behavior such as root mean square (RMS) velocities were studied as a function of dimensionless particle relaxation time ( ) by using a Lagrangian approach. Combination of SISM in GLBE with particle tracking analysis in turbulent channel flow is novelty of the present work. Both GLBE and SISM solve the flow field equations locally. This is an advantage of this method and makes it easy implementing. Comparison of the present results with previous available data indicated that SISM in GLBE is a reliable method for simulation of turbulent flows which is a key point to predict particles behavior correctly.http://jafmonline.net/JournalArchive/download?file_ID=39830&issue_ID=228Generalized lattice Boltzmann equation Large eddy simulation Particle tracking Fluid mean velocity Fluid root-mean-square (RMS) fluctuation velocity Particle mean velocity Particle root-mean-square (RMS) fluctuation velocity. |
| spellingShingle | Mandana Samari Kermani Saeed Jafari Mazyar Salmanzadeh Mohamad Rahnama Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method Journal of Applied Fluid Mechanics Generalized lattice Boltzmann equation Large eddy simulation Particle tracking Fluid mean velocity Fluid root-mean-square (RMS) fluctuation velocity Particle mean velocity Particle root-mean-square (RMS) fluctuation velocity. |
| title | Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method |
| title_full | Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method |
| title_fullStr | Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method |
| title_full_unstemmed | Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method |
| title_short | Investigation of Particles Statistics in large Eddy Simulated Turbulent Channel Flow using Generalized lattice Boltzmann Method |
| title_sort | investigation of particles statistics in large eddy simulated turbulent channel flow using generalized lattice boltzmann method |
| topic | Generalized lattice Boltzmann equation Large eddy simulation Particle tracking Fluid mean velocity Fluid root-mean-square (RMS) fluctuation velocity Particle mean velocity Particle root-mean-square (RMS) fluctuation velocity. |
| url | http://jafmonline.net/JournalArchive/download?file_ID=39830&issue_ID=228 |
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