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Robustness in Numerical Computation II Validated ODE Solver

Robustness in Numerical Computation II Validated ODE Solver. Kwang Hee Ko School of Mechatronics Gwangju Institute of Science and Technology. Solving ODEs. Traditional ODE solvers: Runge-Kutta, Adams-Bashforth, etc. Work well in general. When two solution features are close to each other

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Robustness in Numerical Computation II Validated ODE Solver

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  1. Robustness in Numerical Computation IIValidated ODE Solver Kwang Hee Ko School of Mechatronics Gwangju Institute of Science and Technology

  2. Solving ODEs • Traditional ODE solvers: Runge-Kutta, Adams-Bashforth, etc. • Work well in general. • When two solution features are close to each other • the step size selection becomes complex • Incorrect step size may lead to a critical problem • Looping or straying

  3. Solving ODEs • Traditional ODE solvers: Runge-Kutta, Adams-Bashforth, etc. • Such problems happen since they control the size of each step solely based on controlling just the error alone. • Do not consider the existence and uniqueness of solution.

  4. Validated Interval ODE Solver • Tracing intersection curves • Use the Validated ODE Solver • Phase I: Step size selection and a priori enclosure computation • Determination of a region where existence and uniqueness of the solution is validated. • Phase II: Tight enclosure computation • Given an a priori enclosure, a tight enclosure at the next step is computed minimizing the wrapping effect. • Using compute a tight enclosure

  5. True solution curve Solution si si+1 si+2 Error bounds Parameter Validated Interval ODE Solver • Conceptual Illustration of Validated ODE Solver.

  6. Validated Interval ODE Solver • Phase I: Step size selection and a priori enclosure computation • To compute a step-size hj and an a priori enclosure such that, Ex. Constant Enclosure Method Tight Enclosure

  7. Validated Interval ODE Solver • Phase II: Tight enclosure computation • Avoid the wrapping effect. • QR decomposition method

  8. Validated Interval ODE Solver • Example

  9. Application to Surface-to-Surface Intersections • In most cases, Rational Parametric Polynomial surface intersections are common. • Solution Methods • Lattice Method • Subdivision Method • Marching Method (Tracing method) • Marching Method is a popular choice.

  10. Derivation!!! Whiteboard!!!

  11. Example: Bicubic–Bezier Intersection • Two rational bicubic-bezier patches. • Starting point found by interval projected polyhedron(IPP) algorithm. "Computation of the Solutions of Nonlinear Polynomial Systems" by E. C. Sherbrooke and N. M. Patrikalakis, Computer Aided Geometric Design, 10, No. 5, (1993) 379-405

  12. Output from the Validated ODE Solver • With respect to the arc length parameter the a priori enclosures of the pre-images of the surfaces are connected.

  13. 3D Mapping of the Parameter Boxes s – t u – v

  14. Intersection of the Boxes in 3D • Collections of boxes obtained from the mapping from each of the surfaces, contain the true solution. • Take union of the set of boxes obtained from each surface. • Take intersection of the two previously constructed sets. • During the intersection, we can in general obtain a substantial reduction in model space error. • The above is related to, and nicely complements, our previous work on interval solids. ”Topological and Geometric Properties of Interval Solid Models" by T. Sakkalis, G. Shen and N. M. Patrikalakis, Graphical Models. Vol. 63, No. 3, pp. 163-175, May 2001

  15. Intersection Approximated by an Interval B-Spline • The result can be expressed as an interval B-spline curve. • Substantial reduction of data storage. • Essentially expressed as two B-spline curves representing, • Spine curve. • An error curve representing half-width. • Slight increase in the width of the model space bound. Approximation of measured data with interval B-splines. S. T. Tuohy, T. Maekawa, G. Shen and N. M. Patrikalakis. Computer-Aided Design, Vol. 29, No. 11, pp. 791-799, 1997.

  16. Variation with Tolerance Rel. Tolerance = 2.6x10-4 Rel. Tolerance = 1.4x10-2

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