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Multiphase code development for simulation of PHELIX experiments

Multiphase code development for simulation of PHELIX experiments. M.E. Povarnitsyn , N.E. Andreev, O.F. Kostenko, K.V. Khischenko and P.R. Levashov Joint Institute for High Temperatures RAS , Moscow , Russia povar@ihed.ras.ru. EMMI Workshop GSI, Darmstadt, Germany 22 November, 2008.

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Multiphase code development for simulation of PHELIX experiments

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  1. Multiphase code development for simulation of PHELIX experiments M.E. Povarnitsyn, N.E. Andreev, O.F. Kostenko, K.V. Khischenko and P.R. Levashov Joint Institute for High Temperatures RAS, Moscow, Russia povar@ihed.ras.ru EMMI Workshop GSI, Darmstadt, Germany 22 November, 2008

  2. Outline • Motivation • PHELIX setup parameters and targets • Model and problems of realization • — Multiscale and multistage tasks • — Adaptive mesh refinement • — Summary of our model • Preliminary results • Conclusions and future plans • Discussion

  3. Setup parameters & tasks  = 1.053 mkm,  ~ 500 fs 10 ns, E ~ 200  500 J, F ~ 1015  1018 W/cm2 Foils & clusters PHELIX • Actual questions: • warm dense matter • increase absorption efficiency • high temperature and ionization • radiation loss Hybrid: metals, dielectrics

  4. space, nm time, fs plasma cloud pulse duration 106 106 foil thickness el-ion exchange laser wavelength 103 103 cluster size skin layer ionization rate laser frequency 100 100 Time & space scales for PHELIX setup

  5. Limitations of modeling QMC ~ 100 particles MD ~ 1 mkm3(~105processors, Blue Gene etc.) Hydrodynamics – real size systems, but… …kinetic models

  6. 1000 mkm 1 mkm Multiscale problem PHELIX Time steps ~ 105 Uniform mesh 2D ~ 106 108 cells 3D ~ 109 1012 cells AMR 2D ~ 105 107 cells 3D ~ 107 1010 cells Expecting AMR profit 2D ~ 10 times 3D ~ 100 times 1000 mkm

  7. Adaptive mesh refinement Refinement is applied in zones of interest (interfaces, high gradients of parameters) while the rest of domain is resolved on a coarse mesh

  8. Δt/4 Δt/2 Δt/4 Δt Δt/4 Δt/2 Δt/4 Advance in time (3 levels of AMR) t lev2 lev1 lev0

  9. Multi-material Godunov’s framework with AMR Pb powder on Al at 5 km/s Grid: 4x106 cells, 104 Pb particles (0.1 mm) 12 proc, 10 hours

  10. Multiscale problem Time steps ~ 105 Uniform mesh 2D ~ 106 108 cells 3D ~ 109 1012 cells AMR 2D ~ 105 107 cells 3D ~ 107 1010 cells Expected AMR profit 2D ~ 10 times 3D ~ 100 times

  11. Two-temperature multi-materialEulerian hydrodynamics Basic equations Mixture model

  12. j+1 U*t j j-1 i i+1 i-1 U* Interface reconstruction algorithm 2D 3D (b) (a) (d) (c) D. Youngs (1987) D. Littlefield (1999) Symmetric difference approximation or some norm minimization is used to determine unit normal vector (e) Specific corner and specific orientation choice makes only five possible intersections of the cell

  13. bn unstable sp Two-temperature semi-empirical EOS

  14. Ablation of metal targets by fs pulses M. E. Povarnitsyn et al. // PRB 75, 235414 (2007). M. E. Povarnitsynet al. // Appl.Surf.Sci.253, 6343 (2007) M. E. Povarnitsynet al. // Appl.Surf.Sci. (in press, 2008)

  15. Extra effects in hot plasma

  16. Model & code features • Multi-material hydrodynamics (several substances + phase transitions) • Two-temperature model (Te  Ti) • Two-temperature equations of state (Khishchenko) • Wide-range models of el-ion collisions, conductivity, heat conductivity (, , ) • Model of laser energy absorption (electromagnetic field) • Model of ionization & recombination (metals, dielectrics) • Model of radiation loss (bremsstrahlung + spectral radiation) • Parallel realization with AMR

  17. Model & code features • Multi-material hydrodynamics (several substances + phase transitions) • Two-temperature model (Te  Ti) • Two-temperature equations of state (Khishchenko) • Wide-range models of el-ion collisions, conductivity, heat conductivity (, , ) • Model of laser energy absorption (electromagnetic field) • Model of ionization & recombination (metals, dielectrics) • Model of radiation loss (bremsstrahlung + spectral radiation) • Parallel realization with AMR

  18. I, a.u. t, ns 6 3 9 12 0 Interaction with Al foil I0 = 5x1011 W/cm2, =1.054 mkm, thickness = 2 mkm, Gauss r0 = 6 mkm single-proc problem domain single-proc Single-processor mode, uniform mesh

  19. Interaction with Al foil I0 = 5x1011 W/cm2, =1.053 mkm, thickness = 2 mkm, Gauss r0 = 6 mkm

  20. Interaction with Cu clusters (ne/ncr)  = 1.053 mkm I0=1017 W/cm2  =500 fs

  21. Interaction with Cu clusters (ne/ncr)  = 1.053 mkm I0=1017 W/cm2  =500 fs

  22. Conclusions and Outlook • Simulation results are sensitive to the models used: absorption, thermal conductivity, electron-ion collisions, EOS, etc… • Interaction with cluster targets can produce warm dense matter with exceptional parameters • Adaptive mesh refinement can give an essential profit in runtime and work memory used • For 2D and 3D simulation of PHELIX experiments we develop hydro-electro code with AMR and in parallel • Multidimensional calculations with AMR and in parallel are in sight

  23. Discussion

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