IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v423y2015icp33-50.html
   My bibliography  Save this article

An efficient numerical method for simulating multiphase flows using a diffuse interface model

Author

Listed:
  • Lee, Hyun Geun
  • Kim, Junseok

Abstract

This paper presents a new diffuse interface model for multiphase incompressible immiscible fluid flows with surface tension and buoyancy effects. In the new model, we employ a new chemical potential that can eliminate spurious phases at binary interfaces, and consider a phase-dependent variable mobility to investigate the effect of the mobility on the fluid dynamics. We also significantly improve the computational efficiency of the numerical algorithm by adapting the recently developed scheme for the multiphase-field equation. To illustrate the robustness and accuracy of the diffuse interface model for surface tension- and buoyancy-dominant multi-component fluid flows, we perform numerical experiments, such as equilibrium phase-field profiles, the deformation of drops in shear flow, a pressure field distribution, the efficiency of the proposed scheme, a buoyancy-driven bubble in ambient fluids, and the mixing of a six-component mixture in a gravitational field. The numerical result obtained by the present model and solution algorithm is in good agreement with the analytical solution and, furthermore, we not only remove the spurious phase-field profiles, but also improve the computational efficiency of the numerical solver.

Suggested Citation

  • Lee, Hyun Geun & Kim, Junseok, 2015. "An efficient numerical method for simulating multiphase flows using a diffuse interface model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 423(C), pages 33-50.
  • Handle: RePEc:eee:phsmap:v:423:y:2015:i:c:p:33-50
    DOI: 10.1016/j.physa.2014.12.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114010693
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2014.12.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Karimipour, Arash & Hemmat Esfe, Mohammad & Safaei, Mohammad Reza & Toghraie Semiromi, Davood & Jafari, Saeed & Kazi, S.N., 2014. "Mixed convection of copper–water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 150-168.
    2. Lee, Hyun Geun & Kim, Junseok, 2008. "A second-order accurate non-linear difference scheme for the N -component Cahn–Hilliard system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(19), pages 4787-4799.
    3. Vanherpe, Liesbeth & Wendler, Frank & Nestler, Britta & Vandewalle, Stefan, 2010. "A multigrid solver for phase field simulation of microstructure evolution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(7), pages 1438-1448.
    4. Foroughi, Sajjad & Jamshidi, Saeid & Masihi, Mohsen, 2013. "Lattice Boltzmann method on quadtree grids for simulating fluid flow through porous media: A new automatic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4772-4786.
    5. Lee, Hyun Geun & Choi, Jeong-Whan & Kim, Junseok, 2012. "A practically unconditionally gradient stable scheme for the N-component Cahn–Hilliard system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1009-1019.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nadja Adam & Florian Franke & Sebastian Aland, 2020. "A Simple Parallel Solution Method for the Navier–Stokes Cahn–Hilliard Equations," Mathematics, MDPI, vol. 8(8), pages 1-14, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hyun Geun Lee & Jaemin Shin & June-Yub Lee, 2019. "A High-Order Convex Splitting Method for a Non-Additive Cahn–Hilliard Energy Functional," Mathematics, MDPI, vol. 7(12), pages 1-13, December.
    2. Lee, Chaeyoung & Jeong, Darae & Shin, Jaemin & Li, Yibao & Kim, Junseok, 2014. "A fourth-order spatial accurate and practically stable compact scheme for the Cahn–Hilliard equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 17-28.
    3. Bahrami, Mehrdad & Akbari, Mohammad & Bagherzadeh, Seyed Amin & Karimipour, Arash & Afrand, Masoud & Goodarzi, Marjan, 2019. "Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 159-168.
    4. Ahmadi Balootaki, Azam & Karimipour, Arash & Toghraie, Davood, 2018. "Nano scale lattice Boltzmann method to simulate the mixed convection heat transfer of air in a lid-driven cavity with an endothermic obstacle inside," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 681-701.
    5. Alsarraf, Jalal & Moradikazerouni, Alireza & Shahsavar, Amin & Afrand, Masoud & Salehipour, Hamzeh & Tran, Minh Duc, 2019. "Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 275-288.
    6. Khaje khabaz, Moahamad & Eftekhari, S. Ali & Hashemian, Mohamad & Toghraie, Davood, 2020. "Optimal vibration control of multi-layer micro-beams actuated by piezoelectric layer based on modified couple stress and surface stress elasticity theories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    7. Hemmat Esfe, Mohammad & Abbasian Arani, Ali Akbar & Esfandeh, Saeed & Afrand, Masoud, 2019. "Proposing new hybrid nano-engine oil for lubrication of internal combustion engines: Preventing cold start engine damages and saving energy," Energy, Elsevier, vol. 170(C), pages 228-238.
    8. Solangi, K.H. & Kazi, S.N. & Luhur, M.R. & Badarudin, A. & Amiri, A. & Sadri, Rad & Zubir, M.N.M. & Gharehkhani, Samira & Teng, K.H., 2015. "A comprehensive review of thermo-physical properties and convective heat transfer to nanofluids," Energy, Elsevier, vol. 89(C), pages 1065-1086.
    9. Mahyari, Amirhossein Ansari & Karimipour, Arash & Afrand, Masoud, 2019. "Effects of dispersed added Graphene Oxide-Silicon Carbide nanoparticles to present a statistical formulation for the mixture thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 98-112.
    10. Lee, Dongsun & Kim, Junseok, 2016. "Comparison study of the conservative Allen–Cahn and the Cahn–Hilliard equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 35-56.
    11. Afrouzi, Hamid Hassanzadeh & Ahmadian, Majid & Moshfegh, Abouzar & Toghraie, Davood & Javadzadegan, Ashkan, 2019. "Statistical analysis of pulsating non-Newtonian flow in a corrugated channel using Lattice-Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    12. Alnaqi, Abdulwahab A. & Sayyad Tavoos Hal, Sina & Aghaei, Alireza & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Predicting the effect of functionalized multi-walled carbon nanotubes on thermal performance factor of water under various Reynolds number using artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 493-500.
    13. Shahsavar, Amin & Bagherzadeh, Seyed Amin & Mahmoudi, Boshra & Hajizadeh, Ahmad & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Robust Weighted Least Squares Support Vector Regression algorithm to estimate the nanofluid thermal properties of water/graphene Oxide–Silicon carbide mixture," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1418-1428.
    14. Hassanzadeh Afrouzi, Hamid & Moshfegh, Abouzar & Farhadi, Mousa & Sedighi, Kurosh, 2018. "Dissipative particle dynamics: Effects of thermostating schemes on nano-colloid electrophoresis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 285-301.
    15. Zhang, Xiaoying & Ma, Funing & Yin, Shangxian & Wallace, Corey D & Soltanian, Mohamad Reza & Dai, Zhenxue & Ritzi, Robert W. & Ma, Ziqi & Zhan, Chuanjun & Lü, Xiaoshu, 2021. "Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review," Applied Energy, Elsevier, vol. 303(C).
    16. Lee, Hyun Geun & Choi, Jeong-Whan & Kim, Junseok, 2012. "A practically unconditionally gradient stable scheme for the N-component Cahn–Hilliard system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1009-1019.
    17. Xiaohong, Dai & Huajiang, Chen & Bagherzadeh, Seyed Amin & Shayan, Masoud & Akbari, Mohammad, 2020. "Statistical estimation the thermal conductivity of MWCNTs-SiO2/Water-EG nanofluid using the ridge regression method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    18. Toghraie, Davood & Karimipour, Arash & Safaei, Mohammad Reza & Goodarzi, Marjan & Alipour, Habibollah & Dahari, Mahidzal, 2016. "Investigation of rib's height effect on heat transfer and flow parameters of laminar water–Al2O3 nanofluid in a rib-microchannelAuthor-Name: Akbari, Omid Ali," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 135-153.
    19. Ghasemi, Ali & Hassani, Mohsen & Goodarzi, Marjan & Afrand, Masoud & Manafi, Sahebali, 2019. "Appraising influence of COOH-MWCNTs on thermal conductivity of antifreeze using curve fitting and neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 36-45.
    20. Karimipour, Arash & D’Orazio, Annunziata & Goodarzi, Marjan, 2018. "Develop the lattice Boltzmann method to simulate the slip velocity and temperature domain of buoyancy forces of FMWCNT nanoparticles in water through a micro flow imposed to the specified heat flux," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 729-745.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:423:y:2015:i:c:p:33-50. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.