Under this section it is possible to set the parameters of the simulation.
TimeStepis the time-step we want to use;
FinTimeis the final physical time at which we want our simulation to stop;
NumStepsis the equivalent of
FinTimebut instead of specifying the physical final time we specify the number of time-steps;
IO_CheckStepssets the number of steps between successive checkpoint files;
IO_InfoStepssets the number of steps between successive info stats are printed to screen;
IO_CFLStepssets the number of steps between successive Courant number stats are printed to screen;
Methodis the time-integration method. Note that only an explicit discretisation is supported.
Orderis the order of the time-integration method.
Variantis the variant of the time-integration method (variables for Runga Kutta:
EQTypeis the tag which specify the equations we want solve:
APEAcoustic Perturbation Equations (variables:
LEELinearized Euler Equations (variables:
Projectionis the type of projection we want to use. Currently, only
AdvectionTypeis the advection operator. Currently, only
WeakDG(classical DG in weak form) is supported.
UpwindTypeis the numerical interface flux (i.e. Riemann solver) we want to use for the advection operator (see  for the implemented formulations):
For the APE operator, the acoustic pressure and velocity perturbations are solved, e.g.:
The LEE use a conservative formulation and introduce the additional density perturbation:
BaseFlowBaseflow (ρ,c2,u) defined by the variables
rho0, c0sq, u0, v0, w0for APE and (ρ,c2,u, γ) defined by
rho0, c0sq, u0, v0, w0, gammafor LEE.
In addition to plain Dirichlet and Neumann boundary conditions, the AcousticSolver features a slip-wall boundary condition, a non-reflecting boundary and a white noise boundary condition.
This BC imposes zero wall-normal perturbation velocity in a way that is more robust than using a Dirichlet boundary condition directly.
The Riemann-Invariant BC approximates a non-reflecting (r.g. Farfield) boundary condition by setting incoming invariants to zero.
The white noise BC imposes a stochastic, uniform pressure at the boundary. The
implementation uses a Mersenne-Twister pseudo random number generator to generate
white Gaussian noise. The standard deviation σ of the pressure is specified by the