Changes between Version 12 and Version 13 of solvers

Timestamp:

10/29/20 11:52:54 (4 years ago)

Author:

tsantos

Comment:

--

solvers

@@ -7 +7 @@
 }}}
 
-Here is an example where biconjugate gradient with block Jacobi preconditioner (bcg) is used only for the stress balance analysis. The direct solver (MUMPS) is used for the rest (mass transport analysis, etc). Also, the recovery solver (MUMPS) is not called if bcg fails in a Picard iteration (linear solver). The only criterion is the mechanical equilibrium, which controls the non-linear solver as a whole. This scheme may compromise the monotonicity of the non-linear solver, but it is faster than calling MUMPS every time bgc fails.
+Here is an example where biconjugate gradient with block Jacobi preconditioner (bcg) is used only for the stress balance analysis. The direct solver (MUMPS) is used for the rest (mass transport analysis, etc). Also, the recovery solver (MUMPS) is not called if bcg fails in a Picard iteration (linear solver step). The only criterion is the mechanical equilibrium, which controls the non-linear solver as a whole. This scheme may compromise the monotonicity and rate of convergence of the non-linear solver, but if the model is too big (>100,000 elements) it is faster than calling MUMPS every time bgc fails.
 
 Note: SSA is very stable, so bcg should convert fast. For HO(3D), bcg may not converge even after 50 iterations. In this case, look at the stress balance convergence (md.verbose=verbose('convergence',true,'solution',true);) and check if it is necessary to relax a little bit the restol value. The scheme below have being used for SSA (~250,000 elements) and for HO (~1,000,000 elements).