StepLinearUVLM

class sharpy.solvers.steplinearuvlm.StepLinearUVLM[source]

Time domain aerodynamic solver that uses a linear UVLM formulation to be used with the solvers.DynamicCoupled solver.

To use this solver, the solver_id = StepLinearUVLM must be given as the name for the aero_solver is the case of an aeroelastic solver, where the setting below would be parsed through aero_solver_settings.

Notes

The integr_order variable refers to the finite differencing scheme used to calculate the bound circulation derivative with respect to time \(\dot{\mathbf{\Gamma}}\). A first order scheme is used when integr_order == 1

\[\dot{\mathbf{\Gamma}}^{n+1} = \frac{\mathbf{\Gamma}^{n+1}-\mathbf{\Gamma}^n}{\Delta t}\]

If integr_order == 2 a higher order scheme is used (but it isn’t exactly second order accurate [1]).

\[\dot{\mathbf{\Gamma}}^{n+1} = \frac{3\mathbf{\Gamma}^{n+1}-4\mathbf{\Gamma}^n + \mathbf{\Gamma}^{n-1}} {2\Delta t}\]

If track_body is True, the UVLM is projected onto a frame U that is:

Coincident with G at the linearisation timestep.

Thence, rotates by the same quantity as the FoR A.

It is similar to a stability axes and is recommended any time rigid body dynamics are included.

See also

sharpy.sharpy.linear.assembler.linearuvlm.LinearUVLM

References

[1] Maraniello, S., & Palacios, R.. State-Space Realizations and Internal Balancing in Potential-Flow Aerodynamics with Arbitrary Kinematics. AIAA Journal, 57(6), 1–14. 2019. https://doi.org/10.2514/1.J058153

The settings that this solver accepts are given by a dictionary, with the following key-value pairs:

Name	Type	Description	Default
`dt`	`float`	Time step	`0.1`
`integr_order`	`int`	Integration order of the circulation derivative. Either `1` or `2`.	`2`
`ScalingDict`	`dict`	Dictionary of scaling factors to achieve normalised UVLM realisation.	`{}`
`remove_predictor`	`bool`	Remove the predictor term from the UVLM equations	`True`
`use_sparse`	`bool`	Assemble UVLM plant matrix in sparse format	`True`
`density`	`float`	Air density	`1.225`
`track_body`	`bool`	UVLM inputs and outputs projected to coincide with lattice at linearisation	`True`
`track_body_number`	`int`	Frame of reference number to follow. If `-1` track `A` frame.	`-1`
`velocity_field_generator`	`str`	Name of the velocity field generator to be used in the simulation	`SteadyVelocityField`
`velocity_field_input`	`dict`	Dictionary of settings for the velocity field generator	`{}`
`vortex_radius`	`float`	Distance between points below which induction is not computed	`sharpy.utils.constants.vortex_radius_def`
`vortex_radius_wake_ind`	`float`	Distance between points below which induction is not computed in the wake convection	`sharpy.utils.constants.vortex_radius_def`
`cfl1`	`bool`	If it is `True`, it assumes that the discretisation complies with CFL=1	`True`

The settings that ScalingDict accepts are the following:

Name	Type	Description	Default
`length`	`float`	Reference length to be used for UVLM scaling	`1.0`
`speed`	`float`	Reference speed to be used for UVLM scaling	`1.0`
`density`	`float`	Reference density to be used for UVLM scaling	`1.0`

initialise(data, custom_settings=None, restart=False)[source]

Initialises the Linear UVLM aerodynamic solver and the chosen velocity generator.

Settings are parsed into the standard SHARPy settings format for solvers. It then checks whether there is any previous information about the linearised system (in order for a solution to be restarted without overwriting the linearisation).

If a linearised system does not exist, a linear UVLM system is created linearising about the current time step.

The reference values for the input and output are transformed into column vectors \(\mathbf{u}\) and \(\mathbf{y}\), respectively.

The information pertaining to the linear system is stored in a dictionary self.data.aero.linear within the main data variable.

Parameters:

data (PreSharpy) – class containing the problem information
custom_settings (dict) – custom settings dictionary

pack_input_vector()[source]

Transform a SHARPy AeroTimestep instance into a column vector containing the input to the linear UVLM system.

\[[\zeta,\, \dot{\zeta}, u_{ext}] \longrightarrow \mathbf{u}\]

If the track_body option is on, the function projects all the input into a frame that:

is equal to the FoR G at time 0 (linearisation point)

rotates as the body frame specified in the track_body_number

Returns:: Input vector
Return type:: np.ndarray

static pack_state_vector(aero_tstep, aero_tstep_m1, dt, integr_order)[source]

Transform SHARPy Aerotimestep format into column vector containing the state information.

The state vector is of a different form depending on the order of integration chosen. If a second order scheme is chosen, the state includes the bound circulation at the previous timestep, hence the timestep information for the previous timestep shall be parsed.

The transformation is of the form:

If integr_order==1:

\[\mathbf{x}_n = [\mathbf{\Gamma}^T_n,\, \mathbf{\Gamma_w}_n^T,\, \Delta t \,\mathbf{\dot{\Gamma}}_n^T]^T\]
Else, if integr_order==2:

\[\mathbf{x}_n = [\mathbf{\Gamma}_n^T,\, \mathbf{\Gamma_w}_n^T,\, \Delta t \,\mathbf{\dot{\Gamma}}_n^T,\, \mathbf{\Gamma}_{n-1}^T]^T\]

For the second order integration scheme, if the previous timestep information is not parsed, a first order stencil is employed to estimate the bound circulation at the previous timestep:

\[\mathbf{\Gamma}^{n-1} = \mathbf{\Gamma}^n - \Delta t \mathbf{\dot{\Gamma}}^n\]

Parameters:

aero_tstep (AeroTimeStepInfo) – Aerodynamic timestep information at the current timestep n.
aero_tstep_m1 (AeroTimeStepInfo) –

Returns:

State vector

Return type:

np.ndarray

run(**kwargs)[source]

Solve the linear aerodynamic UVLM model at the current time step n. The step increment is solved as:

\[\begin{split}\mathbf{x}^n &= \mathbf{A\,x}^{n-1} + \mathbf{B\,u}^n \\ \mathbf{y}^n &= \mathbf{C\,x}^n + \mathbf{D\,u}^n\end{split}\]

A change of state is possible in order to solve the system without the predictor term. In which case the system is solved by:

\[\begin{split}\mathbf{h}^n &= \mathbf{A\,h}^{n-1} + \mathbf{B\,u}^{n-1} \\ \mathbf{y}^n &= \mathbf{C\,h}^n + \mathbf{D\,u}^n\end{split}\]

Variations are taken with respect to initial reference state. The state and input vectors for the linear UVLM system are of the form:

If integr_order==1:
\[\mathbf{x}_n = [\delta\mathbf{\Gamma}^T_n,\, \delta\mathbf{\Gamma_w}_n^T,\, \Delta t \,\delta\mathbf{\dot{\Gamma}}_n^T]^T\]

Else, if integr_order==2:
\[\mathbf{x}_n = [\delta\mathbf{\Gamma}_n^T,\, \delta\mathbf{\Gamma_w}_n^T,\, \Delta t \,\delta\mathbf{\dot{\Gamma}}_n^T,\, \delta\mathbf{\Gamma}_{n-1}^T]^T\]

And the input vector:
\[\mathbf{u}_n = [\delta\mathbf{\zeta}_n^T,\, \delta\dot{\mathbf{\zeta}}_n^T,\,\delta\mathbf{u_{ext}}^T_n]^T\]

where the subscript n refers to the time step.

The linear UVLM system is then solved as detailed in sharpy.linear.src.linuvlm.Dynamic.solve_step(). The output is a column vector containing the aerodynamic forces at the panel vertices.

To Do: option for impulsive start?

Parameters:

aero_tstep (AeroTimeStepInfo) – object containing the aerodynamic data at the current time step
structure_tstep (StructTimeStepInfo) – object containing the structural data at the current time step
convect_wake (bool) – for backward compatibility only. The linear UVLM assumes a frozen wake geometry
dt (float) – time increment
t (float) – current time
unsteady_contribution (bool) – (backward compatibily). Unsteady aerodynamic effects are always included

Returns:

updated self.data class with the new forces and circulation terms of the system

Return type:

PreSharpy

unpack_ss_vectors(y_n, x_n, u_n, aero_tstep)[source]

Transform column vectors used in the state space formulation into SHARPy format

The column vectors are transformed into lists with one entry per aerodynamic surface. Each entry contains a matrix with the quantities at each grid vertex.

\[\mathbf{y}_n \longrightarrow \mathbf{f}_{aero}\]

\[\mathbf{x}_n \longrightarrow \mathbf{\Gamma}_n,\, \mathbf{\Gamma_w}_n,\, \mathbf{\dot{\Gamma}}_n\]

If the track_body option is on, the output forces are projected from the linearization frame, to the G frame. Note that the linearisation frame is:

equal to the FoR G at time 0 (linearisation point)

rotates as the body frame specified in the track_body_number

Parameters:

y_n (np.ndarray) – Column output vector of linear UVLM system
x_n (np.ndarray) – Column state vector of linear UVLM system
u_n (np.ndarray) – Column input vector of linear UVLM system
aero_tstep (AeroTimeStepInfo) – aerodynamic timestep information class instance

Returns:

Tuple containing:

forces (list):
Aerodynamic forces in a list with n_surf entries. Each entry is a (6, M+1, N+1) matrix, where the first 3 indices correspond to the components in x, y and z. The latter 3 are zero.

gamma (list):
Bound circulation list with n_surf entries. Circulation is stored in an (M+1, N+1) matrix, corresponding to the panel vertices.

gamma_dot (list):
Bound circulation derivative list with n_surf entries. Circulation derivative is stored in an (M+1, N+1) matrix, corresponding to the panel vertices.

gamma_star (list):
Wake (free) circulation list with n_surf entries. Wake circulation is stored in an (M_star+1, N+1) matrix, corresponding to the panel vertices of the wake.

Return type:

tuple