Projects per year
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.
Original language | English |
---|---|
Pages (from-to) | 46-53 |
Number of pages | 8 |
Journal | Computers and Fluids |
Volume | 115 |
Early online date | 1 Apr 2015 |
DOIs | |
Publication status | Published - 22 Jul 2015 |
Keywords
- computational fluid dynamics
- design optimisation
- hybrid methods
- molecular dynamics
- Murray's law
- nanofluidics
Fingerprint
Dive into the research topics of 'Enhancing nano-scale computational fluid dynamics with molecular pre-simulations: unsteady problems and design optimisation'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Non-Equilibrium Fluid Dynamics for Micro/Nano Engineering Systems
Reese, J.
EPSRC (Engineering and Physical Sciences Research Council)
1/01/11 → 16/02/16
Project: Research