Engineers have traditionally used continuum equations to model processes, such as the Navier-Stokes equation for fluid flow. These methods require constitutive relations that encode the properties of the fluid; these are typically determined empirically and have limited predictive capabilities. While the continuum description is well established and has become commonplace in engineering calculations, their limitations have become apparent with the increasing use of complex materials (e.g., polymer solutions, nanoparticle suspensions etc.), which may possess underlying mesoscopic structures that can impart intricate behaviours.
In principle, these complex materials can be modelled using molecular scale methods, such as molecular dynamics and Monte Carlo simulations. At these very short length scales, the discrete nature of matter becomes important, and the system is typically treated from a "particle" perspective, where the mathematical focus is on the dynamics of particles and their mutual interactions. The tremendous progress of computational power and algorithmic efficiencies have dramatically extended the range of time and length scales where these methods can be practically applied; these are beginning to reach scales where the continuum description becomes reasonable. However, they are nowhere near practical to use in process scale calculations. Coarse graining approaches have been developed to try to extend the scales at which molecular simulations can be applied, however, these still represent the system as a collection of interacting particles, and, consequently, it is unclear how these methods can transition to the continuum description at large scales, thereby limiting their use as engineering tools.
This ambitious project attempts to build a single, unified description of complex fluids that incorporates molecular-level detail but can be applied on a wide range of length and time scales that extends to the continuum scale. The initial phase of the project will focus on the static properties of the fluid (e.g., thermodynamics and structure); later, the dynamics of the fluid will be examined. This approach will be developed and tested against data from large scale event-driven molecular dynamics simulations, as well as direct numerical simulations of the hydrodynamic equations for compressible flow.
In addition to undertaking cutting edge research, students are also registered for the Postgraduate Certificate in Researcher Development (PGCert), which is a supplementary qualification that develops a student’s skills, networks and career prospects.
Key Words: Statistical Mechanics, Thermodynamics, Fluid Dynamics, Molecular Dynamics, Direct Numerical Simulations
Funding DetailsThis PhD project is initially offered on a self-funding basis. It is open to applicants with their own funding, or those applying to funding sources. However, excellent candidates will be eligible to be considered for a University scholarship.
Primary supervisor - Dr Leo LueSecondary supervisor - Dr Demos Kivotides
Ms Jacqueline Brown
+44(0) 141 574 5319
James Weir Building, 75 Montrose Street, Glasgow, G1 1XJ
How to applyApply for this PhD project here.
Please quote the project title in your application.