comsol_ThermalBlock3D_script.m

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%comsol_ThermalBlock3D_script
%
% This script creates the data needed for a detailed and reduced simulation
% of the Comsol-3D-Thermal-Block model.
% It can be used for testing or just for gettin an overview of the comsol
% functions.
%
% Oliver Zeeb, 2012

%load the model:
fprintf('loading comsol_ThermalBlock3D_model...\n')
model = comsol_ThermalBlock3D_model;
fprintf('done!\n')

%create the data needed for simulation
fprintf('generating model_data...\n')
model_data=gen_model_data(model);
fprintf('done!\n')

%after generation of model data all the needed matrices are stored in
%model_data --> now Comsol is only needed for plotting the results but no
%longer for calculating! Using Matlab instead of Comsol for the calculation
%speeds up things (really much, especially on a Mac!!!)
model.use_comsol=0;

fprintf('generating detailed_data...\n')
detailed_data = gen_detailed_data(model,model_data);
fprintf('done!\n')

fprintf('generating reduced_data...\n')
reduced_data = gen_reduced_data(model,detailed_data);

%check how many parameters there are.
mu_old = get_mu(model);
switch length(mu_old)   
    case 3
        mu = [1,3,9]
    case 8
        mu = [1,2,3,4,5,6,7,8]
    case 125
        mu = 1:125
    otherwise
        error('length of mu doesnt fit to this script!')
end
model=set_mu(model,mu);

%run a reduced Simulation
fprintf(['calculating reduced solution for mu = ' num2str(mu),'...\n']);
rb_sim_data=rb_simulation(model,reduced_data);
rb_sim_data=rb_reconstruction(model,detailed_data,rb_sim_data);
fprintf('done!\n')
figure(1)
plot_sim_data(model,model_data,rb_sim_data,[])
title('reduced solution');

%run a detailled solution
fprintf(['calculating detailed solution for mu = ' num2str(mu),'...\n']);
sim_data=detailed_simulation(model,model_data);
fprintf('done!\n')
figure(2)
plot_sim_data(model,model_data,sim_data,[])
title('detailed solution')

%compare the errors:
fprintf('comparing the L2-error Udet - Ured.\n')
Udet = sim_data.U;
Ured = rb_sim_data.U;
U_diff = abs(Udet-Ured);
L2_error = sqrt(U_diff' * model_data.inner_product_matrices.L2 * U_diff);
fprintf(['\n\nL2-Error is: ', num2str(L2_error),'\n'])