Presentation is loading. Please wait.

Presentation is loading. Please wait.

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.

Similar presentations


Presentation on theme: "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."— Presentation transcript:

1 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 2 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 Outline

3 3 Setup parameters & tasks = 1.053 mkm,  ~ 500 fs  10 ns, E ~ 200  500 J, F ~ 10 15  10 18 W/cm 2 PHELIX Hybrid: metals, dielectrics Foils & clusters Actual questions: warm dense matter increase absorption efficiency high temperature and ionization radiation loss

4 4 Time & space scales for PHELIX setup time, fs pulse duration el-ion exchange ionization rate 10 3 10 0 10 6 laser frequency laser wavelength space, nm plasma cloud cluster size skin layer 10 3 10 0 10 6 foil thickness

5 5 Limitations of modeling QMC ~ 100 particles MD ~ 1 mkm 3 (~10 5 processors, Blue Gene etc.) Hydrodynamics – real size systems, but… …kinetic models

6 6 Multiscale problem 1 mkm 1000 mkm Time steps ~ 10 5 Uniform mesh 2D ~ 10 6  10 8 cells 3D ~ 10 9  10 12 cells AMR 2D ~ 10 5  10 7 cells 3D ~ 10 7  10 10 cells Expecting AMR profit 2D ~ 10 times 3D ~ 100 times PHELIX

7 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 8 Advance in time (3 levels of AMR) ΔtΔt Δt /2 Δt /4 lev0 lev 1 lev2 t

9 9 Multi-material Godunov’s framework with AMR Pb powder on Al at 5 km/s Grid: 4x10 6 cells, 10 4 Pb particles (0.1 mm) 12 proc, 10 hours

10 10 Multiscale problem Time steps ~ 10 5 Uniform mesh 2D ~ 10 6  10 8 cells 3D ~ 10 9  10 12 cells AMR 2D ~ 10 5  10 7 cells 3D ~ 10 7  10 10 cells Expected AMR profit 2D ~ 10 times 3D ~ 100 times

11 11 Two-temperature multi-material Eulerian hydrodynamics Basic equationsMixture model

12 12 Interface reconstruction algorithm (a) (b) (c) (d) (e) D. Youngs (1987) D. Littlefield (1999) Specific corner and specific orientation choice makes only five possible intersections of the cell Symmetric difference approximation or some norm minimization is used to determine unit normal vector j+1 j j-1 i-1 ii+1 U*tU*t U*U* 3D2D

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

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

15 15 Extra effects in hot plasma

16 16 1.Multi-material hydrodynamics (several substances + phase transitions) 2.Two-temperature model (Te  Ti) 3.Two-temperature equations of state (Khishchenko) 4.Wide-range models of el-ion collisions, conductivity, heat conductivity (, ,  ) 5.Model of laser energy absorption (electromagnetic field) 6.Model of ionization & recombination (metals, dielectrics) 7.Model of radiation loss (bremsstrahlung + spectral radiation) 8.Parallel realization with AMR Model & code features

17 17 1.Multi-material hydrodynamics (several substances + phase transitions) 2.Two-temperature model (Te  Ti) 3.Two-temperature equations of state (Khishchenko) 4.Wide-range models of el-ion collisions, conductivity, heat conductivity (, ,  ) 5.Model of laser energy absorption (electromagnetic field) 6.Model of ionization & recombination (metals, dielectrics) 7.Model of radiation loss (bremsstrahlung + spectral radiation) 8.Parallel realization with AMR Model & code features

18 18 Interaction with Al foil 0 3912 t, ns I, a.u. 6 single-proc problem domain single-proc I 0 = 5x10 11 W/cm 2, =1.054 mkm, thickness = 2 mkm, Gauss r 0 = 6 mkm Single-processor mode, uniform mesh

19 19 Interaction with Al foil I 0 = 5x10 11 W/cm 2, =1.053 mkm, thickness = 2 mkm, Gauss r 0 = 6 mkm

20 20 Interaction with Cu clusters (n e /n cr ) #14  [g/cc] 2.8 T e [ev]620 T i [ev]75 = 1.053 mkm I 0 = 10 17 W/cm 2  = 500 fs

21 21 Interaction with Cu clusters (n e /n cr ) #14#6  [g/cc] 2.81 T e [ev]620970 T i [ev]7560 = 1.053 mkm I 0 = 10 17 W/cm 2  = 500 fs

22 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 23 Discussion


Download ppt "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."

Similar presentations


Ads by Google