Recent development of a flowing MHD model for a rotating, collisional plasma column discovered the intriguing prediction of opposite axial acceleration of the plasma ions in the subsonic and supersonic regimes. This project would examine the regime above, below, and through the shock.

In 2017 we published (http://dx.doi.org/10.1088/1361-6587/59/2/025003) a steady-state single fluid MHD model which describes the equilibrium of plasma parameters in a collisional, rotating plasma column with temperature gradients and a non-uniform externally applied magnetic field.  The model, which solved force balance along and across the plasma, was constrained to data from a local plasma physics experiment (MAGPIE) from Langmuir, electric and Mach probes.

An unexpected observation was that in the supersonic regime the axial flow profile is inverted, in other words the flow slows (rather than accelerates) towards the maximum magnetic field gradient region. This behaviour, together with the transition from sub- to supersonic flow, are interesting physics phenomena and may also have application to space propulsion physics.

In this project, we would explore the shock transition in detail, and include shock physics across the transition.  A possible experimental outcome would be to identify conditions under which a shock might form, leading to the possibility of experimental verification. The project is well defined, and suitable as an Honours project (or an entree to a PhD) for students with an interest and skills in theoretical modelling and interpretation of data.

A further possibility is to include a neutral fluid population in the physics model via addition of a conservation of momentum equation for the neutral species, and also resolve neutral-ion collisions. This project would be appropriate in scale to a 3^rd year special projects student, and/or could be expanded to include an honours project.

Experimental Mach probe measurements of the on-axis axial velocity for a hydrogen plasma in MAGPIE (blue), together with theory predictions (red).