simulation_data = lin_evol_rb_simulation_primal_dual(model, reduced_data) More...
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Functions | |
function
simulation_data = | lin_evol_rb_simulation_primal_dual (model, reduced_data) |
simulation_data = lin_evol_rb_simulation_primal_dual(model, reduced_data) More... | |
simulation_data = lin_evol_rb_simulation_primal_dual(model, reduced_data)
Definition in file lin_evol_rb_simulation_primal_dual.m.
function simulation_data = lin_evol_rb_simulation_primal_dual | ( | model, | |
reduced_data | |||
) |
simulation_data = lin_evol_rb_simulation_primal_dual(model, reduced_data)
function, which performs a reduced basis online simulation for the parameter vector mu, which is assumed to be set in the model class, i.e. a previous model = model.set_mu(model,[...]) is assumed to have taken place.
allowed dependency of data: Nmax, N, M, mu not allowed dependency of data: H allowed dependency of computation: Nmax, N, M, mu not allowed dependency of computation: H Unknown at this stage: —
Required fields of model as required by the numerical operators mu_names : the cell array of names of mu-components and for each of these stringt, a corresponding field in model is expected. T : end-time of simulation nt : number of timesteps to compute error_norm : l2
L_I_inv_norm_bound: upper bound on implicit operator inverse norm constant in time, a single scalar L_E_norm_bound: upper bounds on explicit operator constant in time, a single scalar
if model.name_output_functional is set, then additionally, a sequence of output estimates s(U(:,))
and error bound Delta_s is returned
see the ***_gen_reduced_data() routine for specifications of the fields of reduced_data
model | model |
reduced_data | reduced data |
simulation_data | simulation data |
want_improved_output —
want improved output want_dual —
want dual verbose —
flag indicating the verbosity level of informative output error_norm —
error norm starting_time_step —
starting time step nt —
number of time steps for evolution discretizations T —
end time for evolution problems dt —
time step size for evolution discretizations L_I_inv_norm_bound —
L I inv norm bound L_E_norm_bound —
L E norm bound use_scm —
use scm constant_LB —
constant LBdual_sim_data —
dual sim data dual_Delta —
dual Delta a0 —
a0 Delta0 —
Delta0 m_I —
m I m_E —
m E m —
m LL_I —
LL I LL_E —
LL E K_II —
K II K_IE —
K IE K_EE —
K EE K_IdId —
K IdId K_IdE —
K IdE bb —
bb LL_I_correct —
LL I correct LL_E_correct —
LL E correct bb_correct —
bb correct N —
N s_RB —
s RB s_l2norm —
s l2normdata_const_in_time —
if this flag is set, then only operators for first time instance are computed name_output_functional —
if this field is existent, then an output estimation is performed and error.estimtations starting_tim_step —
in t-partition case this is the starting time step for the actual t-partitioni time step stopping_time_step —
in t-partition this is the stopping time step for the actual t-partitiona —
time sequence of solution coefficients, columns are a
( — ,k)' = \(a^(k-1)\) Delta —
time sequence of \(L^2\)-posteriori error estimates Delta(k)
= \(\Delta^{k-1}_N\) or energy-norm-posterior error estimates Delta_energy(k)
= \(\bar \Delta^{k-1}_N\) depending on the field "error_norm" in model. s —
s Delta_s —
Delta s Definition at line 17 of file lin_evol_rb_simulation_primal_dual.m.