Hi all,
I made a thermoelasticity model based on the cantilever example, reduced_basis_ex5, by adding a new temperature variable. At the beginning of the basis training procedure, the maximum error bound drops sharply from 1.35694e+07 to 41 as the dimension of the basis increases from 0 to 5. After that, although the basis dimension keeps growing, the error bound stops decreasing and stays at a certain number. The relative training tolerance is set at 1.e-7 and the mesh is a T-shaped pipe. ---- Basis dimension: 5 ---- Performing RB solves on training set Maximum error bound is 2.42578 Performing truth solve at parameter: h: 1.055972e+01 h_Tinf: 2.472563e+02 heat_flux: 4.261782e+01 ---- Basis dimension: 6 ---- Performing RB solves on training set Maximum error bound is 2.43818 Performing truth solve at parameter: h: 1.151397e+01 h_Tinf: 2.473108e+02 heat_flux: 4.481571e+01 ---- Basis dimension: 7 ---- Performing RB solves on training set Maximum error bound is 2.44673 Exiting greedy because the same parameters were selected twice The RB result obtained from this basis differs a lot from the FEM result. I searched archives of the mailing list and found that this phenomenon might result from an overly low training tolerance. However, the initial error bound being nearly e+07, if I select a less strict tolerance, I will end up having an unsatisfying error and probably a worse result. Could you please suggest me some advice? I would be grateful for your response. Best regards, Gauvain ------------------------------------------------------------------------------ Check out the vibrant tech community on one of the world's most engaging tech sites, Slashdot.org! http://sdm.link/slashdot _______________________________________________ Libmesh-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/libmesh-users
