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

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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 (https://doi.org/10.1016/j.compfluid.2015.03.023)

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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.

ORCID iDs

Holland, David M., Borg, Matthew K., Lockerby, Duncan A. and Reese, Jason M. ORCID logoORCID: https://orcid.org/0000-0001-5188-1627;
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