Dear Mr./Ms.，
In fact, I want to solve a discretized equation like this where K, U=[u1u2 …un]Tand F are fields sit on the vertices, and can easily be created by ‘DMCreateMatrix’ or ‘DMCreateGlobalVector’. λ is the Lagrange multiplier vector. The augmented Q (non-square) is the constraint coefficient matrix and has the form as The Q is employed here to satisfy the following constraints So how to build the entire system in-place in one big matrix (Kλ)? Could you give me more specific suggestions on this problem? Thank you very much! Best regards, Yahe -----原始邮件----- 发件人:"Barry Smith" <[email protected]> 发送时间:2022-04-07 23:10:20 (星期四) 收件人: "Matthew Knepley" <[email protected]> 抄送: "高亚贺" <[email protected]>, PETSc <[email protected]> 主题: Re: [petsc-users] question DMStag may also be useful for your needs (and far simpler to use than DMPLEX) depending on where your Lagrange multipliers live. Note that regardless you should not need to be copying entire large submatrices around into bigger matrices; you can build the entire system in-place in one big matrix. MatNest is also a possibility depending on exactly what you are doing. If you explain what your Lagrange multipliers are (the constraints) we may be able to make more specific suggestions. Barry On Apr 7, 2022, at 8:26 AM, Matthew Knepley <[email protected]> wrote: On Thu, Apr 7, 2022 at 8:16 AM 高亚贺 via petsc-users <[email protected]> wrote: Dear Mr./Ms.， I have used ‘DMCreateMatrix’ to create a matrix K, and also the ‘DMCreateGlobalVector’ to create two vectors U (to be solved) and F (right-hand side), i.e. KU=F. Now, I want to add some complex constraints to this system through lagrangian multiplier method, and the constraint matrix is Q. The KU=F transforms to <1649328463919.png> How to create Kλ, and how to effectively copy values K and Q to Kλ? Does the newly created Kλ and Fλ still have an advantage of DMDA? Or do you have any other good suggestions for this kind of problem? DMDA can only really handle collocated discretizations, meaning all fields sit on the vertices. If you can discretize your problem this way, then just give it two fields and assemble K_\lambda as normal. If not, then you might look at DMPlex which supports a wider range of discretizations. Thanks, Matt Thank you very much! Best regards, A PETSc user -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener https://www.cse.buffalo.edu/~knepley/
About the problem of Lagrange multiplier.docx
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