- Volumes 84-95 (2024)
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Volumes 72-83 (2023)
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Volume 83
Pages 1-258 (December 2023)
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Volume 82
Pages 1-204 (November 2023)
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Volume 81
Pages 1-188 (October 2023)
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Volume 80
Pages 1-202 (September 2023)
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Volume 79
Pages 1-172 (August 2023)
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Volume 78
Pages 1-146 (July 2023)
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Volume 77
Pages 1-152 (June 2023)
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Volume 76
Pages 1-176 (May 2023)
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Volume 75
Pages 1-228 (April 2023)
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Volume 74
Pages 1-200 (March 2023)
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Volume 73
Pages 1-138 (February 2023)
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Volume 72
Pages 1-144 (January 2023)
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Volume 83
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Volumes 60-71 (2022)
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Volume 71
Pages 1-108 (December 2022)
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Volume 70
Pages 1-106 (November 2022)
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Volume 69
Pages 1-122 (October 2022)
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Volume 68
Pages 1-124 (September 2022)
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Volume 67
Pages 1-102 (August 2022)
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Volume 66
Pages 1-112 (July 2022)
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Volume 65
Pages 1-138 (June 2022)
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Volume 64
Pages 1-186 (May 2022)
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Volume 63
Pages 1-124 (April 2022)
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Volume 62
Pages 1-104 (March 2022)
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Volume 61
Pages 1-120 (February 2022)
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Volume 60
Pages 1-124 (January 2022)
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Volume 71
- Volumes 54-59 (2021)
- Volumes 48-53 (2020)
- Volumes 42-47 (2019)
- Volumes 36-41 (2018)
- Volumes 30-35 (2017)
- Volumes 24-29 (2016)
- Volumes 18-23 (2015)
- Volumes 12-17 (2014)
- Volume 11 (2013)
- Volume 10 (2012)
- Volume 9 (2011)
- Volume 8 (2010)
- Volume 7 (2009)
- Volume 6 (2008)
- Volume 5 (2007)
- Volume 4 (2006)
- Volume 3 (2005)
- Volume 2 (2004)
- Volume 1 (2003)
• An extended LBM approach for solving RANS equations coupled with k−ɛ turbulence model was developed.
• The simulation results were compared with available experimental data and numerical simulation.
• LBM–RANS yields a reasonably accurate description of turbulent flows at modest computational cost.
Using the lattice-Boltzmann computational approach in conjunction with the Reynolds averaged Navier–Stokes (RANS) model, several turbulent flows and the transport and deposition of particles in different passages were studied. The new lattice Boltzmann method (LBM) solved the RANS equations coupled with the standard and renormalization group k−ɛ turbulence models. In particular, the LBM formulation was augmented by the addition of two transport equations for the probability distribution function of populations of k and ɛ. The discrete random walk model was used to generate the instantaneous turbulence fluctuations. For turbulent channel flows, the analytical fits to the root mean-square velocity fluctuations obtained by the direct numerical simulation of the turbulent flow were used in the analysis. Attention was given to the proper evaluation of the wall normal turbulent velocity fluctuations particularly near the wall. The simulation results were compared with the available numerical simulation and experimental data. The new LBM–RANS model is shown to provide a reasonably accurate description of turbulent flows and particle transport and deposition at modest computational cost.