Hi Nek's,<br><br>Given a random initial vector u and the Jacobian matrix of the linearized Navier-Stokes, I would like to calculate the matrix-vector product J * u. In Nek, that would consists in calculating only the right hand side of the equations, that is:<br>
<br><div style="margin-left: 40px;">RHS = ( -U.grad(u) - u.grad(U) - grad(p) + 1/Re Lap(u) ; div(u) )<br clear="all"></div><br>I have a few questions on how to compute those different terms in userchk (Nek is used in post-process mode):<br>
<ul><li>I would tend to use convop() for the convection terms, however I'm not sure whereas it would output the strong or weak form (and I need the strong one obviously)?</li><li>Same question regarding grad(p) and div(u) if I use opgradt() and opdiv() to calculate them?</li>
</ul>Last but not least, for the Laplacian I've read a previous mail where it is said that it can be computed using a sequence of wgradm1() and vec_dssum() so I guess I kown how to compute at the strong form for it.<br>
<br>Sincerely,<br>-- <br>Jean-Christophe<br>