rolland.discretization.DiscretizationEBBVertic¶

class rolland.discretization.DiscretizationEBBVertic(*args, **kwargs)[source]¶

Bases: Discretization

Abstract base class for FDM discretization according to Stampka and Sarradj [4].

Discretizes the differential equation and can be applied either with constant or time-dependent parameters, which is the case, for example, with a moving sound source.

Parameters:

args (t.Any)
kwargs (t.Any)

track¶

Track instance.

Type:: Track

dt¶

Step size in time \([s]\).

Type:: float

req_simt¶

Requested simulation time \([s]\).

Type:: float

bx¶

Stability coefficient for dx calculation (must be \(b_x \geq 1\)) \([-]\).

Type:: float

nt¶

Number of time steps \([-]\).

Type:: int

sim_t¶

Actual simulation time \([s]\).

Type:: float

dx¶

Step size in space \([m]\).

Type:: float

bx_upd¶

Updated stability coefficient \([-]\).

Type:: float

nx¶

Number of spatial steps \([-]\).

Type:: int

bound¶

Boundary instance.

Type:: PMLRailDampVertic

n_bound¶

Number of spatial steps in single sided boundary domain \([-]\).

Type:: int

pml¶

Damping array for boundary domain.

Type:: numpy.ndarray

A¶

Coefficient matrix A.

Type:: scipy.sparse.csc_matrix

B¶

Coefficient matrix B.

Type:: scipy.sparse.csc_matrix

C¶

Coefficient matrix C.

Type:: scipy.sparse.csc_matrix

calc_grid()[source]¶: Calculate grid parameters.

calc_bound()[source]¶: Calculate boundary properties.

build_matrix(vec_dr, vec_sp, vec_dp, vec_ms, vec_sb, vec_db)[source]¶

Build matrices A, B, and C according to Stampka and Sarradj [4].

Parameters:

vec_dr (numpy.ndarray) – Rail damping vector.
vec_sp (numpy.ndarray) – Pad stiffness vector.
vec_dp (numpy.ndarray) – Pad damping vector.
vec_ms (numpy.ndarray) – Sleeper/Slab mass vector.
vec_sb (numpy.ndarray) – Ballast stiffness vector.
vec_db (numpy.ndarray) – Ballast damping vector.

Return type:

None

abstractmethod validate_discretization_stampka()[source]¶: Validate the discretization according to Stampka.