1 / 50

To Dream the Impossible Scheme

To Dream the Impossible Scheme. Part 1 Approximating Derivatives on Non-Uniform, Skewed and Random Grid Schemes Part 2 Applying Rectangular Finite Difference Schemes to Non-Rectangular Regions to Approximate Solutions to Partial Differential Equations.

Download Presentation

To Dream the Impossible Scheme

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. To Dream the Impossible Scheme Part 1 Approximating Derivatives on Non-Uniform, Skewed and Random Grid Schemes Part 2 Applying Rectangular Finite Difference Schemes to Non-Rectangular Regions to Approximate Solutions to Partial Differential Equations

  2. Approximating Derivatives on Non-Uniform, Skewed and Random, Grid Schemes Skewed Non-Uniform Random

  3. Approximating Derivativesfrom a Data Table How do we approximate f’(.5)

  4. Approximating Derivativesfrom a Data Table 2-Point Forward Difference Approximation

  5. Approximating Derivativesfrom a Data Table 2-Point Backward Difference Approximation

  6. Approximating Derivativesfrom a Data Table 2-Point Central Difference Approximation

  7. Approximating Derivativesfrom a Data Table In Summary … so Far Which is right? Which is better?

  8. Approximating Derivativesfrom a Data Table 3-PT FD Approx

  9. Approximating Derivativesfrom a Data Table 4-PT CD Approximation Note the new compact notation:

  10. Approximating Derivativesfrom a Data Table 5-PT FD Approximation:

  11. Approximating Derivativesfrom a Data Table In Summary Which is the best approximation?

  12. Approximating Derivativesfrom a Data Table

  13. 2-point FD: 2-point CD: 3-point FD: 4-point CD: 5-point FD: Estimates of the 1st Derivative (CRC)

  14. 2nd D,2-point CD : 3rd D, 4-point FD: 3rd D, 4-point CD: 4th D, 5-point FD: 4th D, 5-point CD: Estimates of Higher Order Derivatives (CRC)

  15. What’s Missing?

  16. Where do these Equations Come From • Derivation starts with the Taylor Series centered on x: • i.e: • Or in a shorthand form the you will see on the following slides:

  17. Derivation of 2-Point BD Equation for the 1st Derivative on a Uniform Grid Start with Three 3-Term Taylor Series Expansions. Where: fn=f(x0+nδ) where δis the grid spacing. Note: Equation for f0is expanded for use in further derivation Note: Define 00=1

  18. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid Multiply Each Equation by a Weight ωn . Note: Error term dropped for the time being for brevity

  19. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid Sum up the Coefficients to Generate the 1st Derivative Expression .

  20. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid A little algebraic manipulation …

  21. Derivation of 2-Point BD Equation for the 1st Derivative on a Uniform Grid And rewritten as a matrix equation … Note: A Vandermonde Matrix

  22. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid A General Vandermonde Matrix

  23. Cofactor Expansion Determinant of a Vandermonde matrix Solving for ω-2 Using Cramer’s Rule

  24. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid Solve for the Remaining Weights. Now use weights to calculate the coefficient of the remainder term …

  25. Derivation of 3-Point BD Equation for the 1st Derivative on a Uniform Grid Voila! .

  26. Derivation of 3-Point BD Equation for the 2nd Derivative on a Uniform Grid Alter RHS Slightly….

  27. Derivation of 5-PointCD Equation for the 3rd Derivative on a Uniform GriD (or, if I desire, anything up to the 4th Derivative) (or, if I desire, anything up to the 4th Derivative)

  28. System will also Work for Skew Grid Schemes (i.e. use backward 1st and 4th point and forward 1st , 2nd, and 6th point to findthe 3rd derivative on a uniform grid) Note: The grid is “uniform”, the spacing between the points is not.

  29. A General Matrix System (for an r-point approximation for the ith derivative) an: integer that describes position of grid point with respect to center point (i.e. anΔx).

  30. Using Cramer's Rule to Solve for ωa1

  31. Which “Simplifies” to: Cofactor Expansion About the 1st Column and The (i+1)th Row Determinant of a Vandermonde matrix

  32. Vandermonde Matrix with the rth row and nth column removed. Minor of the Vandermonde Matrix With the (i+1)th row and nth column removed (from previous slide). Schur polynomial of order r-i-1 Turning our Attention to the Numerator … T. Ernst, Generalized Vendermonde Systems of Equations. Mathematics of Computation, 24, (1970) 893-903. I.G. Macdonald, Symmetric Functions and Hall Polynomials, Oxford Mathematical Mongraphs, Second Ed. 1995. S.D. Marchi, Polynomials arising in factoring generalized Vandermonde determinants: An algorthm for computing their coefficients, The Mathematical and Computer Modeling, 34 (2003) 280-287.

  33. Schur Polynomials

  34. Schur Polynomial det(V) Therefore …

  35. Finally … Where ωn is the nth weight for an r-point estimate of the ith derivative with grid points whose relative position to the center is given by {a1, …, ar} and grid spacing is δ.

  36. Recall the Earlier Example … (i.e. use backward 1st and 4th point and forward 1st , 2nd, and 6th point to estimatethe 3rd derivative on a uniform grid) Note: The grid is “uniform”, the spacing between the points is not.

  37. Using Algorithm Generates …

  38. It also Generates the 4th Derivative…

  39. The Extension to Random Grids… A slight adjustment to this equation will accomplish this. Let δ=1 and ai be the position from the point of interest.

  40. Applying Finite Difference Schemes to Non-Rectangular Regions

  41. The Wave Equationon a Circular Membrane Object: Solve analytically using the polar from of the wave equation. Then compare to a numerical finite difference approximation that superimposes a rectangular grid on the circle. Note that the grid size varies from point to point on the circle.

  42. Wave Equation: Rectangular Form: Polar Form: Polar Form: (Radial Symmetry) The Wave Equation

  43. PDE (ω=1, 0≤r ≤1): Boundary Conditions: Initial Conditions: Boundary/Initial Conditions

  44. Analytic Solution Jm: Bessel Function of the First Kind of order m μmn: Is the ntheigenvalue of Jm

  45. Numeric Solution Since the grid is rectangular, use the rectangular form of the wave equation: The discrete form of this equation from finite difference methods Note: Based on 3-point central difference formulations of the spatial terms. Note: Based on 3-point backward difference formulation in time. Note: The time grid is uniform.

  46. Numeric Solution Time Stepping: Stability Requirement: Δt ≤ smallest grid increment

  47. DemonstrationUsing 3-pt CD Formulations

  48. Future ResearchApply to More Complex Regions

More Related