Analysis of Mesh Resolution Effect to Numerical Result of CFD-ROM: Turbulent Flow in Stationary Parallel Plate

Authors

  • Candra Damis Widiawaty Department of Mechanical Engineering, Politeknik Negeri Jakarta, Depok 16424, Indonesia
  • Ahmad Indra Siswantara Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
  • Muhammad Arif Budiyanto Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
  • Mohammad Arif Andira Air Research Group, Depok, Indonesia
  • Dendy Adanta Department of Mechanical Engineering, Faculty of Engineering, Universitas Sriwijaya, Ogan Ilir-30662, South Sumatera, Indonesia
  • Muhammad Hilman Gumelar Syafe’i Mechanical Engineering, Universitas Negeri Semarang, Semarang 50229, Jawa Tengah, Indonesia
  • Tanwir Ahmad Farhan Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
  • Illa Rizianiza Mechanical Engineering, Institut Teknologi Kalimantan, Karangjoang Kalimantan Timur 76127, Indonesia

DOI:

https://doi.org/10.37934/cfdl.16.8.117

Keywords:

Turbulent, Mesh Resolution, CFD-ROM

Abstract

Computational fluid dynamics (CFD) is extensively utilized to predict flow behaviour in various industries and applications. The Full Order Model (FOM) is a high-accuracy approach to flow modelling, but it requires significant computational resources due to its high order and thousands of variables. To address this problem, the Reduced Order Model (ROM) was developed. Despite the advancement brought by ROM, there is a notable gap in research concerning the impact of mesh configuration on CFD-ROM results. While the number of modes has been extensively studied for its influence on CFD-ROM, the mesh configuration, a critical aspect of the simulation process, has received relatively limited attention. This study investigates the effect of mesh resolution on numerical results in CFD-ROM concerning turbulent flow within stationary parallel plates. Employing rigorous methods, including Richardson Extrapolation, verification, validation, and error percentage. The results explicitly confirm that mesh resolution directly impacts the numerical results of the velocity field in CFD-ROM. It is found that there is a notable reduction in Convergence Grid Index (CGI) values for different mesh ratios: 6.401% for medium-to-coarse and 2.031% for fine-to-medium ratio. Thus, with the same mode number, mesh resolution selection can enhance the numerical result of the velocity field in CFD-ROM.

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Author Biographies

Candra Damis Widiawaty, Department of Mechanical Engineering, Politeknik Negeri Jakarta, Depok 16424, Indonesia

candra.damis.widiawati@mesin.pnj.ac.id

Ahmad Indra Siswantara, Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia

a_indra@eng.ui.ac.id

Muhammad Arif Budiyanto, Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia

arief@eng.ui.ac.id

Mohammad Arif Andira, Air Research Group, Depok, Indonesia

ariefandira0209@gmail.com

Dendy Adanta, Department of Mechanical Engineering, Faculty of Engineering, Universitas Sriwijaya, Ogan Ilir-30662, South Sumatera, Indonesia

dendyadanta@ymail.com

Muhammad Hilman Gumelar Syafe’i, Mechanical Engineering, Universitas Negeri Semarang, Semarang 50229, Jawa Tengah, Indonesia

m.hilman@mail.unnes.ac.id

Tanwir Ahmad Farhan, Department of Mechanical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia

tanwirtaf@gmail.com

Illa Rizianiza, Mechanical Engineering, Institut Teknologi Kalimantan, Karangjoang Kalimantan Timur 76127, Indonesia

rizianiza@lecturer.itk.ac.id

References

Krastev, Vesselin Krassimirov, Luca Silvestri, and Gino Bella. "Effects of turbulence modeling and grid quality on the zonal URANS/LES simulation of static and reciprocating engine-like geometries." SAE International Journal of Engines 11, no. 6 (2018): 669-686. https://doi.org/10.4271/2018-01-0173

Xu, Guangping, and Jiasong Wang. "CFD modeling of particle dispersion and deposition coupled with particle dynamical models in a ventilated room." Atmospheric Environment 166 (2017): 300-314. https://doi.org/10.1016/j.atmosenv.2017.07.027

Ramdlan, G. Gun Gun, Ahmad Indra Siswantara, Asyari Daryus, and Hariyotejo Pujowidodo. "Turbulence model and validation of air flow in wind tunnel." International Journal of Technology 7, no. 8 (2016): 1362-1371. https://doi.org/10.14716/ijtech.v7i8.6891

Siswantara, Ahmad Indra, Budiarso, and Steven Darmawan. "Investigation of Inverse-Turbulent-Prandtl Number with Four RNG k-ε Turbulence Models on Compressor Discharge Pipe of Bioenergy Micro Gas Turbine." Applied Mechanics and Materials 819 (2016): 392-400.

https://doi.org/10.4028/www.scientific.net/AMM.819.392

Widiawaty, C. D., A. I. Siswantara, G. G. R. Gunadi, H. Pujowidodo, and M. H. G. Syafei. "A CFD simulation and experimental study: predicting heat transfer performance using SST k-ω turbulence model." In IOP Conference Series: Materials Science and Engineering, vol. 909, no. 1, p. 012004. IOP Publishing, 2020. https://doi.org/10.1088/1757-899X/909/1/012004

Widiawaty, Candra Damis, Ahmad Indra Siswantara, Budiarso Budiarso, Asyari Daryus, Gun Gun Ramdlan Gunadi, and Hariyotejo Pujowidodo. "Investigation the effect of superficial velocity to the heat transfer in bubbling regime of fluidization using CFD simulation." In AIP Conference Proceedings, vol. 2187, no. 1. AIP Publishing, 2019. https://doi.org/10.1063/1.5138279

Wang, Kan, Tingting Shi, Yuru He, Mingzhi Li, and Xinming Qian. "Case analysis and CFD numerical study on gas explosion and damage processing caused by aging urban subsurface pipeline failures." Engineering Failure Analysis 97 (2019): 201-219. https://doi.org/10.1016/j.engfailanal.2019.01.052

Khanjanpour, Mohammad Hassan, and Akbar A. Javadi. "Optimization of a Horizontal Axis Tidal (HAT) turbine for powering a Reverse Osmosis (RO) desalination system using Computational Fluid Dynamics (CFD) and Taguchi method." Energy Conversion and Management 231 (2021): 113833. https://doi.org/10.1016/j.enconman.2021.113833

Blazek, Jiri. Computational fluid dynamics: principles and applications. Butterworth-Heinemann, 2015. https://doi.org/10.1016/B978-0-08-099995-1.00012-9

van Leer, Bram, and Kenneth G. Powell. "Introduction to computational fluid dynamics." Encyclopedia of Aerospace Engineering (2010). https://doi.org/10.1002/9780470686652.eae048

Sciacchitano, A., F. Arpino, and G. Cortellessa. "Benchmark PIV database for the validation of CFD simulations in a transitional cavity flow." International Journal of Heat and Fluid Flow 90 (2021): 108831. https://doi.org/10.1016/j.ijheatfluidflow.2021.108831

Centeno-González, Felipe Orlando, Electo Eduardo Silva Lora, Helcio Francisco Villa Nova, Lourival Jorge Mendes Neto, Arnaldo Martín Martínez Reyes, Albert Ratner, and Mohsen Ghamari. "CFD modeling of combustion of sugarcane bagasse in an industrial boiler." Fuel 193 (2017): 31-38. https://doi.org/10.1016/j.fuel.2016.11.105

Weinman, K. A., M. Fragner, Ralf Deiterding, Daniela Heine, Uwe Fey, F. Braenstroem, B. Schultz, and Claus Wagner. "Assessment of the mesh refinement influence on the computed flow-fields about a model train in comparison with wind tunnel measurements." Journal of Wind Engineering and Industrial Aerodynamics 179 (2018): 102-117. https://doi.org/10.1016/j.jweia.2018.05.005

Stabile, Giovanni, Saddam Hijazi, Andrea Mola, Stefano Lorenzi, and Gianluigi Rozza. "POD-Galerkin reduced order methods for CFD using Finite Volume Discretisation: vortex shedding around a circular cylinder." Communications in Applied and Industrial Mathematics 8, no. 1 (2017): 210-236. https://doi.org/10.1515/caim-2017-0011

Schilders, Wil. "Introduction to model order reduction." In Model order reduction: theory, research aspects and applications, pp. 3-32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. https://doi.org/10.1007/978-3-540-78841-6_1

Gao, Xi, Tingwen Li, William A. Rogers, Kristin Smith, Katherine Gaston, Gavin Wiggins, and James E. Parks II. "Validation and application of a multiphase CFD model for hydrodynamics, temperature field and RTD simulation in a pilot-scale biomass pyrolysis vapor phase upgrading reactor." Chemical Engineering Journal 388 (2020): 124279. https://doi.org/10.1016/j.cej.2020.124279

Georgaka, Sokratia, Giovanni Stabile, Kelbij Star, Gianluigi Rozza, and Michael J. Bluck. "A hybrid reduced order method for modelling turbulent heat transfer problems." Computers & Fluids 208 (2020): 104615. https://doi.org/10.1016/j.compfluid.2020.104615

Liu, Yang, Wuxuan Pan, and Zhengwei Long. "Optimization of air supply parameters for stratum ventilation based on proper orthogonal decomposition." Sustainable Cities and Society 75 (2021): 103291. https://doi.org/10.1016/j.scs.2021.103291

Zimmermann, Ralf. "Gradient-enhanced surrogate modeling based on proper orthogonal decomposition." Journal of Computational and Applied Mathematics 237, no. 1 (2013): 403-418. https://doi.org/10.1016/j.cam.2012.06.010

Gullberg, Rebecca. "Computational fluid dynamics in OpenFOAM." Mesh Generation and Quality. TKP 4555 (2017).

Zhang, Jun, Farzin Darihaki, and Siamack A. Shirazi. "A comprehensive CFD-based erosion prediction for sharp bend geometry with examination of grid effect." Wear 430 (2019): 191-201. https://doi.org/10.1016/j.wear.2019.04.029

Wang, Shan, Jorge Gadelho, Hafizul Islam, and C. Guedes Soares. "CFD modelling and grid uncertainty analysis of the free-falling water entry of 2D rigid bodies." Applied Ocean Research 115 (2021): 102813. https://doi.org/10.1016/j.apor.2021.102813

Shao, Yingjuan, Jinrao Gu, Wenqi Zhong, and Aibing Yu. "Determination of minimum fluidization velocity in fluidized bed at elevated pressures and temperatures using CFD simulations." Powder Technology 350 (2019): 81-90. https://doi.org/10.1016/j.powtec.2019.03.039

Slotnick, Jeffrey P., Abdollah Khodadoust, Juan Alonso, David Darmofal, William Gropp, Elizabeth Lurie, and Dimitri J. Mavriplis. CFD vision 2030 study: a path to revolutionary computational aerosciences. No. NF1676L-18332. 2014.

Deep, Dewanshu, Ashwin Sahasranaman, and S. Senthilkumar. "POD analysis of the wake behind a circular cylinder with splitter plate." European Journal of Mechanics-B/Fluids 93 (2022): 1-12. https://doi.org/10.1016/j.euromechflu.2021.12.010

Sanderse, Benjamin. "Non-linearly stable reduced-order models for incompressible flow with energy-conserving finite volume methods." Journal of Computational Physics 421 (2020): 109736. https://doi.org/10.1016/j.jcp.2020.109736

Hami, Khelifa. "Turbulence Modeling a Review for Different Used Methods." International Journal of Heat & Technology 39, no. 1 (2021). https://doi.org/10.18280/ijht.390125

Masatsuka, Katate. I do Like CFD, vol. 1. Vol. 1. Lulu. com, 2009.

Launder, Brian Edward, and Dudley Brian Spalding. "The numerical computation of turbulent flows." In Numerical prediction of flow, heat transfer, turbulence and combustion, pp. 96-116. Pergamon, 1983. https://doi.org/10.1016/B978-0-08-030937-8.50016-7

Calzolari, Giovanni, and Wei Liu. "Deep learning to replace, improve, or aid CFD analysis in built environment applications: A review." Building and Environment 206 (2021): 108315. https://doi.org/10.1016/j.buildenv.2021.108315

Ballarin, Francesco, Andrea Manzoni, Alfio Quarteroni, and Gianluigi Rozza. Supremizer stabilization of POD-Galerkin approximation of parametrized Navier-Stokes equations. MATHICSE Technical Report, École Polytechnique Fédérale de Lausanne, 2014. https://doi.org/10.1002/nme.4772

Stabile, Giovanni, and Gianluigi Rozza. "Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations." Computers & Fluids 173 (2018): 273-284. https://doi.org/10.1016/j.compfluid.2018.01.035

Lande, Anne Marie. "Complex mesh generation with openfoam." Master's thesis, University of South-Eastern Norway, 2021.

ITHACA-FV, “06POD_RBF.C.” [Online]. Available: https://mathlab.github.io/ITHACA-FV/06POD_RBF_8C-example.html.

Silvestri, Luca. "CFD modeling in Industry 4.0: New perspectives for smart factories." Procedia Computer Science 180 (2021): 381-387. https://doi.org/10.1016/j.procs.2021.01.359

Tu, Jiyuan, Guan Heng Yeoh, Chaoqun Liu, and Yao Tao. Computational fluid dynamics: a practical approach. Elsevier, 2018.

cfdsof, “No Title.” [Online]. Available: https://cfdsof.com/.

Mavriplis, Dimitri J. "Mesh generation and adaptivity for complex geometries and flows." In Handbook of computational fluid mechanics, pp. 417-459. Academic Press, 1996. https://doi.org/10.1016/B978-012553010-1/50008-6

Widiawaty, Candra Damis, Ahmad Indra Siswantara, Gun Gun R. Gunadi, Mohamad Arif Andira, Muhammad Arif Budiyanto, M. Hilman Gumelar Syafei, and Dendy Adanta. "Optimization of inverse-Prandtl of Dissipation in standard k-ε Turbulence Model for Predicting Flow Field of Crossflow Turbine." CFD Letters 14, no. 1 (2022): 112-127. https://doi.org/10.37934/cfdl.14.1.112127

Roache, Patrick J., Kirti N. Ghia, and Frank M. White. "Editorial policy statement on the control of numerical accuracy." Journal of Fluids Engineering 108, no. 1 (1986): 2. https://doi.org/10.1115/1.3242537

Yunus, A. Cengel. Fluid Mechanics: Fundamentals And Applications (Si Units). Tata McGraw Hill Education Private Limited, 2010.

Published

2024-03-31

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