Enhancing nano-scale computational fluid dynamics with molecular pre-simulations: Unsteady problems and design optimisation. (22nd July 2015)

• Record Type: Journal Article
• Authors: Holland, David M.; Borg, Matthew K.; Lockerby, Duncan A.; Reese, Jason M.
• Is Part Of: Computers & fluids. Volume 115(2015)
• Page Start: 46
• Page End: 53
• Publication Date: 2015-07-22
• Subjects: Nanofluidics -- Computational fluid dynamics -- Molecular dynamics -- Hybrid methods -- Design optimisation -- Murray's Law; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2015.03.023
• Languages: English
• ISSNs: 0045-7930

Abstract

Highlights: Nano-scale unsteady flows are modelled through a converging–diverging channel. Excellent agreement is found between our CFD model and full MD simulations. A design optimisation procedure is performed on a nano-scale network of channels. A disparity between the macro-scale (Murray's law) and nano-scale solutions is found. An alternative to Murray's Law is derived to include slip effects at boundaries. 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.