Enhancing nano-scale computational fluid dynamics with molecular pre-simulations : unsteady problems and design optimisation

Holland, David M. and Borg, Matthew K. and Lockerby, Duncan A. and Reese, Jason M. (2015) Enhancing nano-scale computational fluid dynamics with molecular pre-simulations : unsteady problems and design optimisation. Computers and Fluids, 115. pp. 46-53. ISSN 0045-7930

[img]
Preview
 Text (Holland-etal-CAF-2015-Enhancing-nano-scale-computational-fluid-dynamics-with-molecular-pre-simulations-unsteady-problems)
Holland_etal_CAF_2015_Enhancing_nano_scale_computational_fluid_dynamics_with_molecular_pre_simulations_unsteady_problems.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (1MB)| Preview

    Abstract

    We demonstrate that a computational fluid dynamics (CFD) model enhanced with molecular-level information can accurately predict unsteady nano-scale flows in non-trivial geometries, while being efficient enough to be used for design optimisation. We first consider a converging-diverging nano-scale channel driven by a time-varying body force. The time-dependent mass flow rate predicted by our enhanced CFD agrees well with a full molecular dynamics (MD) simulation of the same configuration, and is achieved at a fraction of the computational cost. Conventional CFD predictions of the same case are wholly inadequate. We then demonstrate the application of enhanced CFD as a design optimisation tool on a bifurcating two-dimensional channel, with the target of maximising mass flow rate for a fixed total volume and applied pressure. At macro scales the optimised geometry agrees well with Murray's Law for optimal branching of vascular networks; however, at nanoscales, the optimum result deviates from Murray's Law, and a corrected equation is presented.

    Creators(s): Holland, David M., Borg, Matthew K., Lockerby, Duncan A. and Reese, Jason M. ORCID logoORCID: https://orcid.org/0000-0001-5188-1627;
    Item type:Article
    ID code:54025
    Keywords:computational fluid dynamics, design optimisation, hybrid methods, molecular dynamics, Murray's law, nanofluidics, Mechanical engineering and machinery, Computer Science(all), Engineering(all)
    Subjects:Technology > Mechanical engineering and machinery
    Department:Technology and Innovation Centre > Advanced Engineering and Manufacturing
    Faculty of Engineering > Mechanical and Aerospace Engineering
    Depositing user: Pure Administrator
    Date deposited:20 Aug 2015 09:47
    Last modified:27 May 2020 00:45
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/54025
    Export data:
    CORE (COnnecting REpositories)