Dear Dr. Wolfgang, Thank you very much for the kind reply.
> This is a very difficult operation to do even in sequential computations > unless you have an analytical description of the boundary. That's because > in > principle you would have to compare the current position with all points > (or > at least all vertices) on the boundary -- which is very expensive to do if > you > had to do it for more than just a few points. The situation does not get > better if you are in parallel, because then you don't even know all of the > boundary vertices. Completely realise and agree. The only efficient way to do this sort of operation is to solve an eikonal > equation in which the solution function equals the distance to the > boundary. > You can't solve it exactly, and so whatever distance you get is going to > be a > finite-dimensional approximation of the exact distance function. I have got a basic idea of the equation from Wikipedia. Can you kindly also point me to any references which describe its numerical solution technique? I have no background in mathematics, so I have difficulty in understanding any high level content. Thanks again! On Fri, 11 Feb 2022 at 10:22, Wolfgang Bangerth <bange...@colostate.edu> wrote: > On 2/10/22 21:24, vachanpo...@gmail.com wrote: > > > > Is there a way to get the shortest distance from cell center to a given > > boundary in p::d::Triangulation? What I really want is the wall normal > > distance. Any other suggestions are also welcome. > > This is a very difficult operation to do even in sequential computations > unless you have an analytical description of the boundary. That's because > in > principle you would have to compare the current position with all points > (or > at least all vertices) on the boundary -- which is very expensive to do if > you > had to do it for more than just a few points. The situation does not get > better if you are in parallel, because then you don't even know all of the > boundary vertices. > > The only efficient way to do this sort of operation is to solve an eikonal > equation in which the solution function equals the distance to the > boundary. > You can't solve it exactly, and so whatever distance you get is going to > be a > finite-dimensional approximation of the exact distance function. > > Best > W. > > > -- > ------------------------------------------------------------------------ > Wolfgang Bangerth email: bange...@colostate.edu > www: http://www.math.colostate.edu/~bangerth/ > > -- > The deal.II project is located at http://www.dealii.org/ > For mailing list/forum options, see > https://groups.google.com/d/forum/dealii?hl=en > --- > You received this message because you are subscribed to the Google Groups > "deal.II User Group" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to dealii+unsubscr...@googlegroups.com. > To view this discussion on the web visit > https://groups.google.com/d/msgid/dealii/1df8e903-7124-86e1-2459-9a12a21f17f6%40colostate.edu > . > -- The deal.II project is located at http://www.dealii.org/ For mailing list/forum options, see https://groups.google.com/d/forum/dealii?hl=en --- You received this message because you are subscribed to the Google Groups "deal.II User Group" group. To unsubscribe from this group and stop receiving emails from it, send an email to dealii+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/dealii/CALAVa_zfN377%2BFdGWRexwH6ub64kfSLp73bRYwpfXtpQeWVY3g%40mail.gmail.com.
