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Title: Nano-scale computational fluid dynamics with molecular dynamics pre-simulations
Author: Holland, David M.
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2015
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A procedure for using Molecular Dynamics (MD) simulations to provide essential fl uid and interface properties for subsequent use in Computational Fluid Dynamics (CFD) calculations of nano-scale fluid fl ows is presented. The MD presimulations enable an equation of state, constitutive relations, and boundary conditions to be obtained for any given fl uid/solid combination, in a form that can be conveniently implemented within an otherwise conventional Navier-Stokes solver. The results presented demonstrate that these enhanced CFD simulations are capable of providing good fl ow field results in a range of complex geometries at the nano-scale. Comparison for validation is with full-scale MD simulations here, but the computational cost of the enhanced CFD is negligible in comparison with the MD. It is shown that this enhanced CFD can predict unsteady nano-scale ows in non-trivial geometries. A converging-diverging nano-scale channel is modelled where the fl uid fl ow is driven by a time-varying body force. The time-dependent mass fl ow rate predicted by the enhanced CFD agrees well with a MD simulation of the same configuration. Conventional CFD predictions of the same case are wholly inadequate. It is demonstrated that accurate predictions can be obtained in geometries that are more complex than the planar MD pre-simulation geometry that provides the nano-scale fl uid properties. The robustness of the enhanced CFD is tested by application to water fl ow along a (15,15) carbon nanotube (CNT) and it is found that useful fl ow information can be obtained. The enhnaced CFD model is applied as a design optimisation tool on a bifurcating two-dimensional channel, with the target of maximising mass fl ow 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 the nano-scale, the optimum result deviates from Murray's law, and a corrected equation is presented. However, it is found that as the mass flow rate increases through the channel high pressure losses occur at the junction of the network. These high pressure losses also have an impact on the optimal design of a network.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QD Chemistry