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Grid generation and adaptive refinement

Grid generation and adaptive refinement

Summer Academy 2008, Numerical Methods in Engineering, Herceg Novi, Montenegro

Goran Rakić

March 22, 2012
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  1. Talk 2.08 Grid generation and adaptive refinement Goran Rakić, student

    Faculty of Mathematics, Belgrade Wednesday, 09/03/2008 Summer Academy 2008 Numerical Methods in Engineering Herceg Novi, Montenegro
  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. 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.
  4. Continuum and discrete grids • Evaluating continumm boundary conforming transformation

    in discrete points of logical space gives discrete grid in physical space
  5. 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.
  6. Bilinear maps • Combining normalization and translation for transforming any

    quadralateral physical domain to rectangle to create bilinear maps • One dimension:
  7. Special coordinate systems • Polar, Spherical and Cylindrical • Parabolic

    Cylinder coordinates • Elliptic Cylinder coordinates • ... • And not to forgot, Cartesian grids ...where we all start from
  8. 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
  9. Let's fix ξ and let η go from 0..1: Now

    add ξ direction: Hmm, something is wrong when moving both ξ and η: Left boundary ξ = 1, right boundary
  10. PDE methods for grid generation • Algebraic methods (affine trans.,

    bilinear, TFI) defining a grid geometrically • PDE methods defining requirements for grid mathematically
  11. 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
  12. 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
  13. Thompson's Elliptic PDE grid • The system is solved on

    uniform grid in computational domain which gives coordinate lines in physical domain
  14. 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
  15. 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
  16. Delaunay triangulation • Simple criteria to connect points to form

    conforming, non intersecting unstructured grid
  17. Delaunay triangulation algorithm • Nice incremental algorithm • Introduce new

    point, locally break triangulation and then retriangulate affected part • Flipping algorithm:
  18. 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)
  19. Overlapping (Chimera-) grids • Built using partially overlapping blocks •

    Boundary conditions are exchanged between domains using interpolation • Can combine structured and unstructured sub-grids
  20. 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
  21. 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
  22. 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.
  23. 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
  24. 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