Gabriel Peters
Endenicher Str. 310
53121 Bonn
00491525/5478185
[email protected]
Am 25.04.19 um 15:28 schrieb Wolfgang Bangerth
> On 4/25/19 4:51 AM, [email protected] wrote:
> >
> > std::vector<Vector<double> > solution_old_values(n_q_points);
> >
> > While assembling the system over all cells I call
> >
> > fe_values.get_function_values (solution_old, solution_old_values);
> >
> > In the Step-21 tutorial, they call
> >
> > const double old_s = old_solution_values[q](dim+1);
> >
> > to get the dim+2 component of the vector.
> >
> > Up to here, everything compiles fine, but I dont know how to apply the
> > values
> > correctly
> > Therefore I have the following two questions:
> >
> > Do I simply have to call: const double solution_o =
> > solution_old_values[q](0);
> > to get the velocity component? In fact they are vector-valued, so a double
> > doesn't make sense that much.
>
> Correct. The vector should be a `Tensor<1,dim>` and you would have to copy
> the
> first `dim` components of `solution_old_values[q]` into the tensor. That's
> burdensome, so I would suggest that instead you use extractors:
> std::vector<Tensor<1,dim>> old_velocity_values(n_q_points);
> fe_values[velocities].get_function_values (...);
> and then you already have (only) the velocities and in their right data type.
>
>
> > And thus my second question is: Do I apply the value correctly to the local
> > matrix
> > by calling:
> > local_matrix(i,j) += solution_o * fe_values[velocities].shape_value(i,q) *
> > fe_values[velocities].shape_value(j,q);
>
> This looks funny. You are multiplying a scalar 'solution_o' and phi_i*phi_j
> where the latter two are vectors. This works, of course, but didn't you want
> solution_o to be a vector as well?
Oh thanks I Wrote bullshit.
I wanted solution_o to be vector-valued.
And I want to multiply it with a gradient function. So I want
local_matrix(i,j) += solution_o * fe_values[velocities].shape_gradient(i,q) *
fe_values[velocities].shape_gradient(j,q);
Does this look any better?
>
> You are also missing the JxW.
I left it out to here to keep Notation as Short as possible
Best regards
Gabriel
>
> Best
> W.
>
>
> --
> ------------------------------------------------------------------------
> Wolfgang Bangerth email: [email protected]
> www: http://www.math.colostate.edu/~bangerth/
>
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