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Talk 2.08
              Grid generation
          and adaptive refinement



Wednesday, 09/03/2008

Summer Academy 2008
Numerical Methods in Engineering                           Goran Rakić, student
Herceg Novi, Montenegro                        Faculty of Mathematics, Belgrade
●   The solution of PDE
    can be simplified by a
    well-constructed grid.

                             ●   Grid which is not well
                                 suited to the problem
                                 can lead to instability
                                 or lack of convergence
Logical and physical domain
Requirements for transformation

●   Jacobian of the transformation should be
    non-zero to preserve properties of hosted equations
    (one to one mapping) where Jacobian matrix is:




●   Smooth, orthogonal grids (or grids without small
    angles) usually result in the smallest error.
Additional requirements



●   Grid spacing in physical domain should
    correlate with expected numerical error
Continuum and discrete grids




●   Evaluating continumm boundary conforming
    transformation in discrete points of logical
    space gives discrete grid in physical space
Quick overview
●   Structured grids




●   Unstructured grids




●   Special grids (multiblock, adaptive,...)
Algebraic methods
●   Known functions are used in one, two, or three
    dimensions for transformation




●   Interpolation between pair of boundaries
●   If boundaries are given as data points,
    approximation must be used to fit function to
    data points first.
Bilinear maps
●   Combining normalization and translation for
    transforming any quadralateral physical domain
    to rectangle to create bilinear maps


●   One dimension:
Bilinear maps in two dimensions
●   Two dimensions (vector form):
Special coordinate systems


●   Polar, Spherical and Cylindrical
●   Parabolic Cylinder coordinates
●   Elliptic Cylinder coordinates
●   ...
●   And not to forgot, Cartesian grids
    ...where we all start from
Transfinite interpolation (TFI)


●   Rapid computation (compare to PDE methods)
●   Easy to control point locations
●   Using Lagrange polynomials for blending:
                    ξ, ξ-1, η, η-1
Boundary parametrization... done
Let's fix ξ and let η go from 0..1:



Now add ξ direction:




                                                    Left boundary
Hmm, something is wrong when moving both ξ and η:




 ξ = 1, right boundary
Ta da!
TFI examples (1/2)
TFI examples (2/2)


1




0   1
Topology of a hole
●   Transformation preserves holes
●   But with little magic...
PDE methods for grid generation


●   Algebraic methods (affine trans., bilinear, TFI)
    defining a grid geometrically


●   PDE methods
    defining requirements for grid mathematically
PDE methods for grid generation
●   We have to construct system of PDEs whose
    solutions are boundary conforming grid
    coordinate lines with specified line spacing

●   Solving the system gives grid

●   For large grids the computing time is
    considerable
Thompson's Elliptic PDE grid
●   ξ = F(x,y) and η = G(x,y) are unknowns in
    Poisson eq with condition so x,y boundaries are
    mapped to boundaries of computational domain


    where P and Q defines grid point spacing

●   Then instead solving ξ and η we change
    independent and dependent variables
Thompson's Elliptic PDE grid




●   The system is solved on uniform grid in
    computational domain which gives coordinate
    lines in physical domain
Example copied from the book
Example copied from the book
    Boundary:
PDE methods for grid generation


●   Hyperbolic – when wall boundaries are well
    defined, but far field boundary is left

●   Can be used to smooth out metric
    discontinuities in the TFI
This slide is intentionally left blank.
Unstructured grids
●   Field is in rapid expansion
●   Faster to generate on complex domains
●   Easy local refinement

●   Complex data structure (link matrix or else)
●   Can be generated more automatically even on
    complex domains, compared to structured grids
Delaunay triangulation
●   Simple criteria to connect points to form
    conforming, non intersecting unstructured grid
Delaunay triangulation algorithm
●   Nice incremental algorithm
●   Introduce new point, locally break triangulation
    and then retriangulate affected part

●   Flipping algorithm:
Point generation?
Advancing front generation
●   Construct a grid from boundary informations
●   Connect boundary points to create edges
    (called “front”)
●   Select any edge in front and create its
    perpendicular bisector. On a bisector pick a
    point at the distance d inside the domain
●   In that point, create a circle of radius r, order
    any points inside circle by distance from center
    and for each create triangles with edge vertices
●   Pick up the first triangle that is not intersecting
    edges, and update front (connect, remove edges)
Overlapping (Chimera-) grids
●   Built using partially overlapping blocks
●   Boundary conditions are exchanged between
    domains using interpolation
●   Can combine structured and unstructured
    sub-grids
Adaptive grid refinement
●   We want to reduce error without unnecessary
    computational costs
●   Regions of rapid variations of solution needs
    better resolution
●   Using AGR we can discretize huge domains
    (astrophysics) and/or domains with non-uniform
    variations across regions of interest
●   Save both memory and CPU time
●   Trivial to implement for unstructured grids
Moving grids


●   Solution adaptive methods for time-depended
    PDEs where regions of “rapid variations” moves
    in time (like Burgers' flow equation)

●   Let grid points move with “whatever fronts are
    present” keeping number of grid points constant
Moving grids math
●   Transform PDEs to include time changing grid
    transformation




●   When discretized, time depending grid points
    are also unknowns so one has to find both


    so more equations must be added.
Moving grids math (cont.)


●   New equations should connect grid points
    changing position with equidistribution principle
    of error in computed PDE solution
●   Having an error-monitor function we want it
    to be equal over average on all grid sections
●   They also must prevent rapid grid movement
Moving grid example without any
 real number-crunching shown
Cheating the “Summary” question
●   No method that fits all
●   In structured domains, algebraic methods are
    preferred for speed and simplicity
●   Usually implemented in multi disciplinary
    software packages that goes with CAD
    interface, surface editing and visualization tools
●   Multi-block

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Grid generation and adaptive refinement

  • 1. Talk 2.08 Grid generation and adaptive refinement Wednesday, 09/03/2008 Summer Academy 2008 Numerical Methods in Engineering Goran Rakić, student Herceg Novi, Montenegro Faculty of Mathematics, Belgrade
  • 2. The solution of PDE can be simplified by a well-constructed grid. ● Grid which is not well suited to the problem can lead to instability or lack of convergence
  • 3.
  • 5. Requirements for transformation ● Jacobian of the transformation should be non-zero to preserve properties of hosted equations (one to one mapping) where Jacobian matrix is: ● Smooth, orthogonal grids (or grids without small angles) usually result in the smallest error.
  • 6. Additional requirements ● Grid spacing in physical domain should correlate with expected numerical error
  • 7. Continuum and discrete grids ● Evaluating continumm boundary conforming transformation in discrete points of logical space gives discrete grid in physical space
  • 8. Quick overview ● Structured grids ● Unstructured grids ● Special grids (multiblock, adaptive,...)
  • 9. Algebraic methods ● Known functions are used in one, two, or three dimensions for transformation ● Interpolation between pair of boundaries ● If boundaries are given as data points, approximation must be used to fit function to data points first.
  • 10. Bilinear maps ● Combining normalization and translation for transforming any quadralateral physical domain to rectangle to create bilinear maps ● One dimension:
  • 11. Bilinear maps in two dimensions ● Two dimensions (vector form):
  • 12. Special coordinate systems ● Polar, Spherical and Cylindrical ● Parabolic Cylinder coordinates ● Elliptic Cylinder coordinates ● ... ● And not to forgot, Cartesian grids ...where we all start from
  • 13. Transfinite interpolation (TFI) ● Rapid computation (compare to PDE methods) ● Easy to control point locations ● Using Lagrange polynomials for blending: ξ, ξ-1, η, η-1
  • 14.
  • 16. Let's fix ξ and let η go from 0..1: Now add ξ direction: Left boundary Hmm, something is wrong when moving both ξ and η: ξ = 1, right boundary
  • 20. Topology of a hole ● Transformation preserves holes ● But with little magic...
  • 21.
  • 22. PDE methods for grid generation ● Algebraic methods (affine trans., bilinear, TFI) defining a grid geometrically ● PDE methods defining requirements for grid mathematically
  • 23. PDE methods for grid generation ● We have to construct system of PDEs whose solutions are boundary conforming grid coordinate lines with specified line spacing ● Solving the system gives grid ● For large grids the computing time is considerable
  • 24. Thompson's Elliptic PDE grid ● ξ = F(x,y) and η = G(x,y) are unknowns in Poisson eq with condition so x,y boundaries are mapped to boundaries of computational domain where P and Q defines grid point spacing ● Then instead solving ξ and η we change independent and dependent variables
  • 25. Thompson's Elliptic PDE grid ● The system is solved on uniform grid in computational domain which gives coordinate lines in physical domain
  • 27. Example copied from the book Boundary:
  • 28. PDE methods for grid generation ● Hyperbolic – when wall boundaries are well defined, but far field boundary is left ● Can be used to smooth out metric discontinuities in the TFI
  • 29. This slide is intentionally left blank.
  • 30. Unstructured grids ● Field is in rapid expansion ● Faster to generate on complex domains ● Easy local refinement ● Complex data structure (link matrix or else) ● Can be generated more automatically even on complex domains, compared to structured grids
  • 31. Delaunay triangulation ● Simple criteria to connect points to form conforming, non intersecting unstructured grid
  • 32. Delaunay triangulation algorithm ● Nice incremental algorithm ● Introduce new point, locally break triangulation and then retriangulate affected part ● Flipping algorithm:
  • 34. Advancing front generation ● Construct a grid from boundary informations ● Connect boundary points to create edges (called “front”) ● Select any edge in front and create its perpendicular bisector. On a bisector pick a point at the distance d inside the domain ● In that point, create a circle of radius r, order any points inside circle by distance from center and for each create triangles with edge vertices ● Pick up the first triangle that is not intersecting edges, and update front (connect, remove edges)
  • 35.
  • 36. Overlapping (Chimera-) grids ● Built using partially overlapping blocks ● Boundary conditions are exchanged between domains using interpolation ● Can combine structured and unstructured sub-grids
  • 37.
  • 38. Adaptive grid refinement ● We want to reduce error without unnecessary computational costs ● Regions of rapid variations of solution needs better resolution ● Using AGR we can discretize huge domains (astrophysics) and/or domains with non-uniform variations across regions of interest ● Save both memory and CPU time ● Trivial to implement for unstructured grids
  • 39. Moving grids ● Solution adaptive methods for time-depended PDEs where regions of “rapid variations” moves in time (like Burgers' flow equation) ● Let grid points move with “whatever fronts are present” keeping number of grid points constant
  • 40. Moving grids math ● Transform PDEs to include time changing grid transformation ● When discretized, time depending grid points are also unknowns so one has to find both so more equations must be added.
  • 41. Moving grids math (cont.) ● New equations should connect grid points changing position with equidistribution principle of error in computed PDE solution ● Having an error-monitor function we want it to be equal over average on all grid sections ● They also must prevent rapid grid movement
  • 42. Moving grid example without any real number-crunching shown
  • 43. Cheating the “Summary” question ● No method that fits all ● In structured domains, algebraic methods are preferred for speed and simplicity ● Usually implemented in multi disciplinary software packages that goes with CAD interface, surface editing and visualization tools ● Multi-block