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Now that we have a differentiable assembly operator, we can use to do chordal decomposition by breaking down the large scale sparse SDP constraint into a bunch of small SDP constraints. We still need an equality constraint to specify that the relationship between the large scale sparse matrix K + c * Ksigma == assembleK(Ms) where Ms is the vector of small matrix decision variables of the same size as the element stiffness matrices, i.e. Ms[1] is of size ndofs_per_element x ndofs_per_element. With this formulation, we can then use SDPBarrierAlg of a PercivalAlg to solve the problem efficiently.
The text was updated successfully, but these errors were encountered:
mohamed82008
changed the title
Chordal decomposition and interior point + augmented Lagrangian algorithm for large scale buckling constraints
Chordal decomposition + barrier method + augmented Lagrangian algorithm for large scale buckling constraints
Dec 1, 2021
Now that we have a differentiable assembly operator, we can use to do chordal decomposition by breaking down the large scale sparse SDP constraint into a bunch of small SDP constraints. We still need an equality constraint to specify that the relationship between the large scale sparse matrix
K + c * Ksigma == assembleK(Ms)
whereMs
is the vector of small matrix decision variables of the same size as the element stiffness matrices, i.e.Ms[1]
is of sizendofs_per_element x ndofs_per_element
. With this formulation, we can then use SDPBarrierAlg of a PercivalAlg to solve the problem efficiently.The text was updated successfully, but these errors were encountered: