Prolonged Plasma Fluid Simulations
Some Numerical Results for Zero Boundary Conditions Along the y-Axis
By Linda Stals

A study of the nonlinear behaviour of the Hasegawa-Wakatani equations has been carried out and documented in arXiv:1107.0112. Here we include some additional simulations highlighting the results for periodic boundary conditions along the x-axis and zero boundary conditions along the y-axis.

We found that if both axis have periodic boundary conditions, the (0, ± 1) modes are unstable. If zero boundary conditions are applied to the y-axis, these unstable modes are removed from the system. Eigenvalue analysis of the linear system of equations suggests that the modes along the x-axis will always be stable.

A low mode analysis carried out with aid of the centre manifold showed that for certain choice of parameters, the (±1, ± 1) modes are unstable. However, as additional modes are included in the simulations evidence of bifurcation behaviour becomes apparent. Additional simulations were carried out for βr = β&phi = 0.001, 0.00001 and 0.0000001.

The three movies below show how the potential φ, density r and vorticity 2 φ change with time. The grid size is [0,2π/k]×[0, 2π/k] where k = 1. Click on the image to enlarge. For the Fourier mode simulations, we have only shown a 16×16 section of grid, the actual computational domain may be higher.

Low Mode Example

Results for p = 1, βr = β&phi = 0.001, κ = 1.5, α = 70, 0 t 5000, computational grid size = 128 × 128

According to the low mode analysis, the modes along the x-axis should be damped out, but the (±1, ± 1) modes will, eventually, grow exponentially.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.


High Mode Example

Results for p = 2, βr = β&phi = 0.01, κ = 1.0, α = 1, 0 t 5000 and computational grid size = 128 × 128

We expect to see a growth in the (± 1, ± 1) modes, but the modes along the x-axis are damped out. With the right choice of parameters, the interactions between these modes balance one another out to give stable bifurcation behaviour.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

High Mode Example, βr = β&phi = 0.001

Results for p = 2, βr = β&phi = 0.001, κ = 1.0, α = 1, 0 t 5000 and computational grid size = 128 × 128

The interaction between the growth in the (± 1, ± 1) modes and the dampening of the modes along the x-axis is particularly evident in this example.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

High Mode Example, βr = β&phi = 0.00001

Results for p = 2, βr = β&phi = 0.00001, κ = 1.0, α = 1, 0 t 5000 and computational grid size = 128 × 128

By reducing the value of βr and β&phi additional modes influence the long-term behaviour of the system, but the lower order modes still dominate.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

High Mode Example, βr = β&phi = 0.0000001

Results for p = 2, βr = β&phi = 0.0000001, κ = 1.0, α = 1, 0 t 5000 and computational grid size = 128 × 128

The final example looks at the simulation results for small values of βr and β&phi.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.

PotentialDensity Vorticity
Potential Image. Density Image. Vortisity Image.