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, [email protected]
EMMI WorkshopGSI, Darmstadt, Germany
22 November, 2008
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
Setup parameters & tasks
= 1.053 mkm, ~ 500 fs 10 ns,E ~ 200 500 J, F ~ 1015 1018 W/cm2
PHELIX
Hybrid: metals, dielectrics
Foils & clusters
Actual questions:• warm dense matter• increase absorption efficiency• high temperature and ionization• radiation loss
4
Time & space scales for PHELIX setup
time, fs
pulse duration
el-ion exchange
ionization rate
103
100
106
laser frequency
laser wavelength
space, nm
plasma cloud
cluster size
skin layer
103
100
106
foil thickness
5
Limitations of modeling
QMC ~ 100 particles
MD ~ 1 mkm3 (~105 processors, Blue Gene etc.)
Hydrodynamics – real size systems, but…
…kinetic models
6
Multiscale problem
1 mkm
1000 mkm
100
0 m
km
Time steps ~ 105
Uniform mesh2D ~ 106 108 cells3D ~ 109 1012 cells
AMR2D ~ 105 107 cells3D ~ 107 1010 cells
Expecting AMR profit2D ~ 10 times
3D ~ 100 times
PHELIX
7
Adaptive mesh refinement
Refinement is appliedin zones of interest (interfaces, high gradientsof parameters) while the restof domain is resolvedon a coarse mesh
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 mesh2D ~ 106 108 cells3D ~ 109 1012 cells
AMR2D ~ 105 107 cells3D ~ 107 1010 cells
Expected AMR profit2D ~ 10 times
3D ~ 100 times
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 approximationor some norm minimization is usedto determine unit normal vector
j+1
j
j-1
i-1 i i+1
U*t
U*
3D2D
13
Two-temperature semi-empirical EOS
1
10
1
10
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Density, g/cm3
l+g
(s)
(g)
(s+l)
(l)
Te
mp
era
ture
, kK
Al
s
lg
s+g
s+l
CP
bnunstable
sp
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
Extra effects in hot plasma
)(3
ieeei
Bei TTn
m
mkQ
20 |/|}Im{ LLL EEkIQ
hoteBF
mete r
mTk
,
/,min
0
2
23
62/1
3
16
3
2e
eBrad Zn
mc
e
m
TkQ
eqieie Z
ZnnkS 1
12/12/3
3 1exp
eee
Hi T
I
T
I
T
I
I
IAk
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
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
Interaction with Al foil
0 3 9 12
t, ns
I, a.u.
6
single-proc
problem domain
single-proc
I0 = 5x1011 W/cm2, =1.054 mkm, thickness = 2 mkm, Gauss r0 = 6 mkm
Single-processor mode, uniform mesh
20
Interaction with Cu clusters (ne/ncr)
#14
[g/cc] 2.8
Te [ev] 620
Ti [ev] 75
-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2
0.0
0.2
0.4
0.6
0.8
1.0
I [a
.u.]
time [ps]
0 50 100 150 200 250 300 350 4000
50
100
150
200
250
300
350
4000 50 100 150 200 250 300 350 400
y, n
m
x, nm
1.0E-3
0.010
0.10
1.0
10
= 1.053 mkm
I0 = 1017 W/cm2
= 500 fs
21
Interaction with Cu clusters (ne/ncr)
#14 #6
[g/cc] 2.8 1
Te [ev] 620 970
Ti [ev] 75 60
-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2
0.0
0.2
0.4
0.6
0.8
1.0
I [a
.u.]
time [ps]
0 50 100 150 200 250 300 350 4000
50
100
150
200
250
300
350
4000 50 100 150 200 250 300 350 400
y, n
m
x, nm
1.0E-3
0.010
0.10
1.0
10
= 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