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Multiresolution Analysis in Radiation Transport

Multiresolution Analysis in Radiation Transport. HyeongKae Park and Cassiano R. E. de Oliveira Nuclear and Radiological Engineering Program, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. Outline. Introduction/Motivation FE-P N equations

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Multiresolution Analysis in Radiation Transport

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  1. Multiresolution Analysis in Radiation Transport HyeongKae Park and Cassiano R. E. de Oliveira Nuclear and Radiological Engineering Program, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  2. Outline • Introduction/Motivation • FE-PN equations • Spatial adaptivity • Angular adaptivity • Numerical examples 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  3. Introduction/Motivation • Importance of numerical simulation as a design tool. • Use of deterministic computational simulation to predict the complex radiation fields is becoming increasingly prevalent (new generation of nuclear reactors, space reactors, and multi-physics applications). • Attempts to simulate ever-larger, more complex problems require efficient and robust numerical algorithmic development. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  4. Introduction/Motivation • Accurate and efficient numerical methods for modeling (large) complex systems. • Accuracy of the numerical solution depends on the discretization methods of the independent variables (space, angle, and energy). • The necessary space-angle resolution required to achieve a desired local accuracy varies throughout the problem domain. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  5. Introduction/Motivation • Q: What is the resolution that I should use to solve my radiation transport problem numerically • A: I don’t know – let the method decide 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  6. Introduction/Motivation • Adaptivity as the way forward • Usually, there is no prior knowledge about the resolution requirement to meet the prescribed accuracy. Especially if the problem itself is not known ie inverse problem • Spatial and angular variable are tightly coupled in radiation transport problems. Thus, space-angle coupled adaptivity must be considered (not covered in this talk). 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  7. Classical Finite Element-Spherical Harmonics (FE-PN) Discretization Method 1st order radiation transport equation (steady state, one speed): 2nd order even-parity form of the radiation transport equation: where, Even-parity flux Parity source 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  8. FE-PN Equations • C and G is the integral form of collision operators: • The second order formulation is self-adjoint. Thus we can use an extremum variational principle to formulate FE-PN equations (Ritz-Galerkin method). 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  9. FE-PN Equations • Weak form of the parity equation: • Angular flux approximated by the trial function of the form: • Discretized form of functional: 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  10. FE-PN Equations • Ritz-Galerkin procedure yields system of equations of the form: • The matrix A has a shell structure (for =0, 2, 4,…): “Diffusion” matrix stencil 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  11. Adaptive Strategy • Discretization of system of equations • Solution of discretized system of equations • Measure of the discretization error • Refinement/creation of new discrete system 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  12. Posteriori Error Measurement • Posteriori error measurement provides information where the discretization needs to be altered (refinement or coarsening) to achieve desired accuracy. • Two basic strategy to compute posteriori error measure. • Derivative recovery error estimator (gradient 1st or Hessian 2nd) • Residual based error estimator 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  13. Length of the element edge respect to metric M Shape of element Spatial Adaptivity • Popular choice of error estimator is the derivative recovery. • Gauge of the mesh quality is measured by the length of the element edge and shape of the element. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  14. Hessian Based Spatial Adaptivity • Hessian based adaptivity is suitable for the anisotropic adaptivity • Expanding the solution in Taylor series: • The leading term of the interpolation error ( for linear finite elements) • Interpolation error is defined as: (H=Hessian Matrix) 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  15. Hessian Based Spatial Adaptivity • Hessian Matrix H is outer product of gradient operator. Hessian matrix provides the idea of directional dependent error measure. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  16. Hessian Based Spatial Adaptivity • Hessian matrix can be decomposed into: • Direction of eigenvector with large eigenvalue (magnitude) corresponds to the direction associated with large error. Eigenvector Eigenvalue 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  17. Approximating Hessian Matrix • Galerekin methods are repeatedly applied to calculate first derivative at node. • The Hessian term can be calculated applying Galerkin methods to the calculated first derivative. • L is row summed lumped mass matrix • N is the finite element basis function 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  18. Angular Adaptivity • The degree of anisotropy in angular flux varies widely with space and energy groups. • Highly-anisotropic angular flux region may be largely localized. • Uniform refinement is not computationally efficient. • Local refinement of angular expansion is more desirable. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  19. Angular Adaptivity • Variable angular resolution can be achieved by truncating the angular expansions nodal-wise. • The hierarchical nature of spherical harmonics expansion allows addition of higher moments shell without changing the existing matrix. • Error can be estimated by computing residual of new system with old solution. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  20. Error Measurement for Angular Expansion • Main quantity of interest in radiation transport problem is the scalar flux: • The error and change in error in scalar flux is: • Thus, it is desirable to estimate the change in scalar flux due to the addition of the higher spherical harmonics moment. If the change is small the contribution of the higher moment is negligible. Therefore, we can truncate the angular expansion in that region. 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  21. Error Estimate Using Residual • Scalar flux can be found by: • Then change in error from PN to PN+1 can be approximated by: • The residual of the system going from PN to PN+1 is: 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  22. Algorithm • For L = 1, N • Solve PL equation • Temporary add the PL+1 shell • Calculate residual • For n=1,NODES • Scale residual with diagonal coefficient • If magnitude of scaled residual is small enough discard the nodes • Otherwise keep the node. • Go to next level 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  23. Numerical Example (Advanced Gas-Cooled Reactor) • Spatial adaptivity using Hessian error measure 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  24. Numerical Example ( photon propagation) 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  25. Numerical Example (nuclear reactor lattice) • 2D C5G7MOX benchmark problem • 4 fuel assemblies • Water moderator • 7 groups • Criticality problem 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  26. Numerical Example (P15 approximation) Group 1 Group 4 Group 7 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  27. Numerical Example (% error) 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  28. Numerical Example 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

  29. Conclusions • Adaptive strategies are needed for efficient numerical simulations. • Derivative-based error measure for spatial adaptivity, and residual-based error measure for the angular adaptivity are suitable for the FE-PN equations. • Efficient reduction in degrees-of-freedom is possible using point-wise adaptive spherical harmonics expansion. • Challenge is fully coupled space-angle adaptivity 19th International Conference on Transport Theory, Budapest, Hungary, July 24-30 2005

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