A class for goal-oriented adaptive solution of linear variational problems.
For a linear variational problem of the form: find u in V satisfyinga(u, v) = L(v) for all v in \(\hat V\)
and a corresponding conforming discrete problem: find u_h in V_h satisfyinga(u_h, v) = L(v) for all v in \(\hat V_h\)
and a given goal functional M and tolerance tol, the aim is to find a V_H and a u_H in V_H satisfying the discrete problem such that|M(u) - M(u_H)| < tol
This strategy is based on dual-weighted residual error estimators designed and automatically generated for the primal problem and subsequent h-adaptivity.
Solve such that the estimated error in the functional ‘goal’ is less than the given tolerance ‘tol’
tol (float)The error tolerance