Hello,
I'm very new to Deal.ii and trying to understand it through modifying step-15. However I get the following error. Although it is descriptive I'm unable to figure out the problem:
"error: no match for ‘operator*’ (operand types are ‘const dealii::Tensor<1, 2>’ and ‘__gnu_cxx::__alloc_traits<std::allocator<dealii::Vector<double> > >::value_type {aka dealii::Vector<double>}’)
* old_solution_values[q] "
I am not sure if I understand it, but my initial guess is that it might be related to the sizes of vectors and tensors (for the case of gradients). I tried to take care of them to the best of my understanding.
My bilinear form:
((grad. phi_i, grad.u*phi_j)+(grad. phi_i, u*grad. phi_j))*del.Uj = (grad. phi_i, u*grad.u)
I have modified/added the following lines:
std::vector<Tensor<1, dim>> old_solution_gradients(n_q_points);
std::vector<Vector<double>> old_solution_values(n_q_points, Vector<double>(dim -1));
fe_values.get_function_gradients(present_solution, old_solution_gradients);
fe_values.get_function_values (present_solution, old_solution_values);
Assembly:
for (unsigned int q = 0; q < n_q_points; ++q)
{
for (unsigned int i = 0; i < dofs_per_cell; ++i)
{
for (unsigned int j = 0; j < dofs_per_cell; ++j)
cell_matrix(i, j) +=
(((fe_values.shape_grad(i, q)
*old_solution_gradients[q]
* fe_values.shape_value(j, q))
+
(fe_values.shape_grad(i, q)
* old_solution_values[q]
* fe_values.shape_grad(j, q)))
* fe_values.JxW(q));
cell_rhs(i) -= (fe_values.shape_grad(i, q)
* old_solution_values[q]
* old_solution_gradients[q]
* fe_values.JxW(q));
}
}
I assume old_solution_values[q] should be the correct variable for "u" but when I use present_solution[q] instead (in assembly part, for curiosity ), it is compiled but in the running stage I get the following error message:
"Additional information:
Iterative method reported convergence failure in step 337. The residual in the last step was 22.0585.
This
error message can indicate that you have simply not allowed a
sufficiently large number of iterations for your iterative solver to
converge. This often happens when you increase the size of your problem.
In such cases, the last residual will likely still be very small, and
you can make the error go away by increasing the allowed number of
iterations when setting up the SolverControl object that determines the
maximal number of iterations you allow.
The other situation where
this error may occur is when your matrix is not invertible (e.g., your
matrix has a null-space), or if you try to apply the wrong solver to a
matrix (e.g., using CG for a matrix that is not symmetric or not
positive definite). In these cases, the residual in the last iteration
is likely going to be large."
While the second problem might not be the case could anyone offer some suggestions or explanations on both cases?
Thank you!
Ali