On Wed, Oct 19, 2011 at 3:54 PM, Blaise Bourdin <span dir="ltr"><<a href="mailto:bourdin@math.lsu.edu">bourdin@math.lsu.edu</a>></span> wrote:<br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Hi,<br>
<br>
I am trying to use TS to solve a simple transient problem in an unstructured finite element f90 code.<br>
<br>
1. Section 6.1.1 of the manual refers to a TSSetMatrices function that can be used to set the RHS and LHS matrices, but I can;t find it. Is this section outdated?<br></blockquote><div><br></div><div>Yes. What you want is to use TSSetIFunction() and TSSetIJacobian(). Jed and Sean have added some nice examples under TS</div>
<div>of this, and in the latest release there is a manual section. </div><div> </div><div>Let us you know if these are unclear.</div><div><br></div><div> Thanks,</div><div><br></div><div> Matt</div><div><br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
2. Since we are using unstructured finite elements, the LHS matrix is not the identity. As far as I understand, we have two possible choices:<br>
- Use a mass lumping approximation of the variational identity matrix (mass matrix), M, and use M^{-1}K for the RHS matrix instead of K.<br>
- Use an IMEX method where the implicit matrix is the variational identity M.<br>
Is this right? What is the recommended way?<br>
3. Is src/ts/examples/tests/ex1f.F supposed to work? Is there a fortran or fortran90 example I could start from? I get the following:<br>
galerkin:tests bourdin$ ./ex1f -linear_constant_matrix<br>
1 Procs Avg. error 2 norm NaN NaN euler<br>
galerkin:tests bourdin$ ./ex1f<br>
1 Procs Avg. error 2 norm NaN NaN euler<br>
<br>
Thanks,<br>
<br>
Blaise<br>
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Department of Mathematics and Center for Computation & Technology<br>
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</font></blockquote></div><br><br clear="all"><div><br></div>-- <br>What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead.<br>
-- Norbert Wiener<br>