so solving g the s n ne neutron on transpor ort equation
play

So Solving g the S N Ne Neutron on Transpor ort Equation on Us - PowerPoint PPT Presentation

So Solving g the S N Ne Neutron on Transpor ort Equation on Us Using H High O Order L Lax-Fr Friedrich chs W WENO Fa Fast Sweeping Methods Dean Wang, Tseelmaa Byambaakhuu The Ohio State University Sebastian Schunert Idaho National


  1. So Solving g the S N Ne Neutron on Transpor ort Equation on Us Using H High O Order L Lax-Fr Friedrich chs W WENO Fa Fast Sweeping Methods Dean Wang, Tseelmaa Byambaakhuu The Ohio State University Sebastian Schunert Idaho National Laboratory Zeyun Wu Virginia Commonwealth University M&C 2019, Portland, Oregon, USA August 25-29, 2019

  2. Outline • Background and motivation • Robustness • High order • Efficiency • LF-WENO methods • Theory (Wang 2019) • Numerical properties (Wang 2019, NSE) • Diffusion limit • Conclusion 2

  3. Numerical methods for S N • Finite difference sweeping methods • SD: 1 st -order upwind; positivity preserving • DD: 2 nd -order; not positivity preserving • SC: weighted DD; 2 nd -order; positivity preserving; less accurate than DD for diffusive problems • Short characteristic methods • SC: constant source • LC: linear source & linear incoming flux; positivity preserving? • QC : Quadratic source & quadratic incoming flux; can be made to be positivity preserving (on-going work) • Galerkin methods: LD, FEM, DFEM • High-order • FEM or DFEM can be very robust with stabilization; however may not as efficient as finite difference sweeping methods. 3

  4. Motivation • A sweeping based numerical method is more accurate than DD, and much more robust as well. • A challenging task… • Chen et al. in 2013 proposed Lax-Friedrichs fast sweeping methods for steady-state hyperbolic conservation laws. • A perfect framework for the S N transport equation! 4

  5. S N in 2-D conservative form 𝑔 𝜔 # + 𝑕 𝜔 & + Σ ( 𝜔 = 𝑡 𝜔, 𝑦, 𝑧 where, 𝑔 𝜔 = 𝜈𝜔 , 𝑕 𝜔 = 𝜃𝜔 , 𝑡 𝜔, 𝑦, 𝑧 = 0 1 2 𝜚 𝑦, 𝑧 + 4 2 𝑅 𝑦, 𝑧 5

  6. Finite difference discretization ; >,? − ; 𝑔 <=4 𝑔 <@4 𝑕 <,?=4 B − B 𝑕 <,?@4 >,? > > + + Σ ( 𝜔 <,? = 𝑡 𝜔 <,? , 𝑦 < , 𝑧 ? (1) ∆𝑦 ∆𝑧 𝑗, 𝑘 + 1 2 Where 𝑗 − 1 𝑗 + 1 2 , 𝑘 2 , 𝑘 𝑗, 𝑘 ; 𝑔 <± D E ,? and B 𝑕 <,?± D E are numerical fluxes 𝑗, 𝑘 − 1 2 6

  7. High order WENO fluxes For 2𝐿 − 1 – th order WENO scheme, the 𝐿 numerical fluxes are computed as Q@4 𝑑 LN 𝑔 ; L (2) 𝑔 = ∑ NOP 𝑠 = 0, … , 𝐿 − 1 , <@L=N,? , <= D E ,? which corresponds to 𝐿 different stencils: 𝑇 L 𝑗 = 𝑦 <@L , 𝑧 ? , … , 𝑦 <@L=Q@4 , 𝑧 ? , 𝑠 = 0, … , 𝐿 − 1 . Each of these numerical fluxes is 𝑙– th order accurate. The 2𝐿 − 1 – th order WENO flux is a superposition of all these K numerical fluxes Q@4 ; 𝑥 N ; N 𝑔 <=4 >,? = X 𝑔 (3) <=4 >,? NOP Q@4 𝑥 N = 1 , and are defined as The nonlinear weights 𝑥 N satisfy 𝑥 N ≥ 0 , ∑ NOP [ \ b \ (4) 𝑥 N = 𝛽 N = _`D [ \ , c=d \ . ∑ \]^ 7

  8. Third order WENO (WENO3) For 𝐿 = 2 , the 2 nd -order accurate numerical fluxes for 𝜈 > 0 are given as = 4 <,? + 4 = − 4 <@4,? + p P 4 ; ; 𝑔 > 𝑔 > 𝑔 𝑔 > 𝑔 > 𝑔 <=4,? , (5) <,? <= D <= D E ,? E ,? And the linear weights are given by 𝑒 P = > 𝑒 4 = 4 p , (6) p Smoothness indicators are given by > , > 𝛾 P = 𝜐 P 𝑔 <=4,? − 𝑔 𝛾 4 = 𝜐 4 𝑔 <,? − 𝑔 (7) <,? <@4,? where 𝜐 P = 𝑏 ∗ max 𝑏𝑐𝑡 Σ (<=4,? − Σ (<,? , 𝑏𝑐𝑡 Σ n<=4,? − Σ n<,? ∆𝑦 𝜐 4 = 𝑐 ∗ max 𝑏𝑐𝑡 Σ (<,? − Σ (<@4,? , 𝑏𝑐𝑡 Σ n<,? − Σ n<@4,? ∆𝑦 8

  9. Lax-Friedrichs sweeping framework Define Lax–Friedrichs fluxes: ; vw ; E ,? = ; (8𝑏) 𝑔 <= D 𝑔 <= D E ,? + 𝜔 <=4,? − 𝜔 <,? , 𝑗 = 1, … , 𝑂 # > vz y 𝑕 <,?= D B E = B 𝑕 <,?= D E + 𝜔 <,?=4 − 𝜔 <,? , 𝑘 = 1, … , 𝑂 & (8𝑐) > Then we have E ,? = ; vw ; ; 𝑔 <= D 𝑔 <= D E ,? − 𝜔 <=4,? − 𝜔 <,? > vz E = y 𝑕 <,?= D B 𝑕 <,?= D B E − 𝜔 <,?=4 − 𝜔 <,? > 9

  10. LF-WENO >,? − 𝜏𝜈 >,? + 𝜏𝜈 ; 𝜔 <=4,? − 𝜔 <,? − ; ; ; 𝑔 <=4 𝑔 <@4 𝜔 <,? − 𝜔 <@4,? 2 2 ∆𝑦 − 𝜏𝜃 + 𝜏𝜃 y 𝜔 <,?=4 − 𝜔 <,? − y 𝑕 <,?=4 B 𝑕 <,?@4 B 𝜔 <,? − 𝜔 <,?@4 2 2 > > + + Σ ( 𝜔 <,? ∆𝑧 = 𝑡 𝜔 <,? , 𝑦 < , 𝑧 ? n } ~,• ,# ~ ,& • ∆#@ ; E,• @ ; E,• @ ‚ƒ @ ‚… ∆† @ y @ y ; ; € ~•D € ~`D E } ~•D,• =} ~`D,• „ ~,••D B „ ~,•`D B E } ~,••D =} ~,•`D ∆‡ (9) 𝜔 <,? = E E v w=z ∆† =ˆ ‰ ∆# ∆‡ 10

  11. Computing algorithm • Initialize 𝜔 <,? and 𝑇 <,? • While 𝑓 > etol Ž 1. for 𝑜 = 1: % sweeping in angle ( 𝜈 > 0, 𝜃 > 0 ) 2 for 𝑗 = 1: 𝑂𝑦 % sweeping in x for 𝑘 = 1: 𝑂𝑧 % sweeping in y • Calculate ; N N 𝑔 and B 𝑕 , 𝑙 = 1,2 % Eq (5) <± D <± D E ,? E ,? • Calculate 𝛾 P , 𝛾 4 % Eq (7) • Calculate 𝛽 N , 𝑥 N , 𝑙 = 1,2 % Eq (4) • Calculate ; E ,? and ; 𝑔 <± D 𝑔 <± D % Eq (5) E ,? • Calculate ; ; E ,? and y 𝑔 <± D 𝑕 <± D B % Eq (8) E ,? • Calculate 𝜔 <,? % Eq (9) • Calculate 𝑇 <,? Ž Ž 2. for 𝑜 = 2 + 1: % sweeping in angle ( 𝜈 < 0, 𝜃 > 0 ) > … Ž pŽ 3. for 𝑜 = > + 1: % sweeping in angle ( 𝜈 < 0, 𝜃 < 0 ) 2 … pŽ 4. for 𝑜 = 2 + 1: 𝑂 % sweeping in angle ( 𝜈 > 0, 𝜃 < 0 ) 11

  12. Spatial convergence 12

  13. Manufactured solution 𝜔 𝑦, 𝑧, 𝜈 N , 𝜃 N = 𝑦 p 𝑧 p 2 − 𝑦 p 2 − 𝑧 p 24𝑦 > − 48𝑦 p + 30𝑦 2 − 6𝑦 ’ 𝑧 p 2 − 𝑧 p 𝜈 N 𝑅 N 𝑦, 𝑧 = 4 − Σ “ 𝜚 𝑦, 𝑧 +𝑦 p 2 − 𝑦 p 24𝑧 > − 48𝑧 p + 30𝑧 2 − 6𝑧 ’ 𝜃 N 13

  14. Sweeping convergence rate Σ ( = 1 cm @4 and c =0.6 Σ ( = 5 cm @4 and c =0.6 14

  15. Computational complexity * Computational complexity: the number of grid points x the number of iterations 15

  16. Positivity? Note that LF-WENO3 can be rendered to be positivity preserving using the linear scaling limiter proposed by Zhang and Shu (2010). 16

  17. Diffusion limit of S N 𝑒𝑦 𝜔 • + Σ ( 𝜔 • = Σ n 𝑒 2 𝜚 + 𝑅 𝜈 • 2 0 ‰ Σ ( → Σ “ → 𝜁Σ “ , 𝑅 → 𝜁𝑅 , Scaling — , ™ We have 𝜔 • = > + 𝑃 𝜁 , for 𝜁 → 0 Where 𝜚 satisfies the following diffusion equation − 𝑒 1 𝑒 𝑒𝑦 𝜚 + Σ œ 𝜚 = 𝑅 𝑒𝑦 3Σ › 17

  18. Diffusion limit – smooth solution 4 4 Σ › = Σ ¡ = − 0.8ε , 𝑅 = ε , 𝑀 = 1, ℎ = 0.1 18

  19. Diffusion limit – nonsmooth solution with boundary layer DD LF-WENO3 𝜁 = 0.01 19

  20. Diffusion limit – 2D L×L = 2×2 , h # = h & = 0.2 4 4 Σ › = Σ ¡ = − 0.8ε , 𝑅 = ε , 20

  21. A theoretical result on diffusion limit (Wang 2019, NSE): Δ𝑦 = 𝜁 ¦ ℎ = 𝜁 ⁄ 4 N ℎ 𝑚 = 0: Thick diffusion limit Larsen et al. 1987: 𝑚 = 1: Intermidiate diffusion limit Δ𝑦 = 𝜁 ⁄ 4 N ℎ Δ𝑦 = ℎ 21

  22. Conclusions • LF-WENO3 is a sweeping scheme based on the Lax– Friedrichs fluxes with the WENO reconstruction. • It can achieve better accuracy than DD, and more importantly it possesses good positivity-preserving property. • In addition, LF-WENO3 can achieve almost linear computational complexity with underrelaxation. • Finally, LF-WENO3 has the diffusion limit of 𝑚 = 1/3 , which lies between the thick diffusion regime ( 𝑚 = 0) and the intermediate regime (𝑚 = 1 ). 22

  23. References • W. Chen, C.-S. Chou, and C.-Y. Kao, “Lax-Friedrichs Fast Sweeping Methods for Steady State Problems for Hyperbolic Conservation Laws,” J. Comput. Phys. , 234, 452 (2013) • D. Wang, T. Byambaakhuu, "High Order Lax-Friedrichs WENO Fast Sweeping Methods for the SN Neutron Transport Equation," Nucl. Sci. Eng. , 193, 9, 982 (2019). • X. Zhang, C.-W. Shu, “On maximum-principle-satisfying high order schemes for scalar conservation laws,” J. Comput. Phys. , 229 (2010). • X. Zhang, C.-W. Shu, “On positivity-preserving high order discontinuous Galerkin schemes for compressible Euler equations on rectangular meshes,” J. Comput. Phys. , 229 (2010). • D. Wang, "The Asymptotic Diffusion Limit of Numerical Schemes for the SN Transport Equation," Nucl. Sci. Eng. , (2019). • E. W. Larsen, J. E. Morel, and W. F. Miller Jr., “Asymptotic Solutions of Numerical Transport Problems in Optically Thick, Diffusive Regimes,” J. Comput. Phys., 69, 283 (1987). 23

  24. Thank You! 24

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend