multiscale_buckley_leverett.m

function res = multiscale_buckley_leverett(step)
% function performing the multiscale buckley leverett experiments
%
% step 1: simply call Frederikes test
% step 2: generate rbmatlab micromodel and run detailed simulation
%         as nonlin_evol for different parameters and visualization
%
% later:
%   step 3: generate approximation: empirical interpolation
%   step 4: check empirical_interpolated detailed simulation 
%   step 5: generate reduced model: reduced basis
%   step 6: reduced simulations and error to detailed one
%   ...


% B. Haasdonk 4.5.2010

if (nargin <1)
  step = 1;
end;

plot_params = [];

switch step
 case 1 % step 1: simply call Frederikes test
  err = test(3*10^(-3),0.75,10,300)
 case 2 % call micromodel as nonlin-evol model
  model = multiscale_buckley_leverett_model([]);
  model_data = gen_model_data(model);
  mu = [1,1];
  model = model.set_mu(model,mu);
  sim_data = detailed_simulation(model,model_data);
  plot_sim_data(model, model_data, sim_data, plot_params);
 otherwise
  error('step number unknown')
end;