atomistic molecular simulations for engineering...
TRANSCRIPT
Atomistic molecular simulations
for engineering applications:
methods, tools and results
Jadran Vrabec
Motivation
Simulation methods vary
in their level of detail
The more detail,
the more predictive power
Quantum chemical
methods scale with
O(M3) ─ O(M7)
[M: basis functions]
Force field methods are
favorable with respect to
scaling and thermodynamics
Force fields ─ Thermodynamics
Contain all thermodynamic properties
Static: thermal, caloric, entropic
Dynamic: viscosity, diffusion, thermal conductivity, …
Surface properties, e.g. surface tension
Straightforwardly applicable to mixtures
Excellent predictive power
Technical accuracy
Classical models for molecular interactions
Parameters have a physical interpretation
in geometries, e.g. wetting, adsorption, zeolites, …
in processes, e.g. condensation, flow, …
Directly applicable for the study of fluids
Iso-Butane
Sampling force fields
Molecular dynamics Monte Carlo
ms2: simulation tool for thermodynamic properties
Molecular dynamics / Monte Carlo
Arbitrary mixtures of rigid molecules
Grand equilibrium method (for VLE)
Several classical ensembles
Consistent FORTRAN90 code
Object oriented
All loops vectorized
MD and MC parallelized
3D visualization interface
All static properties (thermal, caloric, entropic)
Gradual insertion for entropic properties
Transport properties (Green-Kubo)
Deublein et al., Comp. Phys. Commun. 182 (2011) 2350
Equation of state for CO2 (Span and Wagner, 1996)
0 ResF, , ,
R T
7
0 0 0 0 0
1 2 3 i i
i 4
, ln a a a ln a ln 1 exp n
i i i i i
7 34t d t d cRes
i i
i 1 i 8
, a a exp
i i
39t d 2 2
i i i i i
i 35
a exp ( ) ( )
Ideal part:
Residual part:
T = 216 … 1100 K, p = 0 … 800 MPa
i
42b 2 2
i i i
i 40
a exp C ( 1) D ( 1)
τ =Tc / T δ = ρ / ρc
Derivatives of the Massieu-Planck potential
)/(RTF mn
nm
nmT
/1 NVT
10
01
20. . .
Any equilibrium thermodynamic property = combination of ´s nm
A total of nine independent
properties sampled per
NVT simulation with ms2
Cyclohexane
Density / mol m-3
Rigid 6CLJ united-atom model by Merker et al., Fluid Phase Equilib. 315 (2012) 77
Cyclohexane
Present simulation data
Span and Wagner, Int. J. Thermophys. 24 (2003) 41
Penoncello et. al., Int. J. Thermophys. 16 (1995) 519
Density / mol m-3
„potential energy“
Cyclohexane
Density / mol m-3
„pressure“
Present simulation data
Span and Wagner, Int. J. Thermophys. 24 (2003) 41
Penoncello et. al., Int. J. Thermophys. 16 (1995) 519
Cyclohexane
Density / mol m-3
„isochoric heat capacity“
Present simulation data
Span and Wagner, Int. J. Thermophys. 24 (2003) 41
Penoncello et. al., Int. J. Thermophys. 16 (1995) 519
Ongoing project with ms2
9 independent thermodynamic data types from one NVT simulation
Generation of an extensive dataset in an automatized fashion
• Parallel execution of (~80 simulation runs) x (9 data points)
Fit of a fundamental EOS in terms of Fres to these data
• EOS may serve for the optimization of the force field
• EOS may be the starting point for technical EOS fitting
Poster T21: Thol, Rutkai, Span, Vrabec:
Molecular simulation of thermodynamic properties and
an equation of state for the Lennard-Jones model fluid
Present status and outlook for ms2
An efficient molecular simulation tool for
thermodynamic properties of homogeneous fluids
New features
Ewald summation for ionic systems
Pair correlations functions
MPI/OpenMP hybrid parallelization
Next development steps
Integer arithmetics
Internal molecular degrees of freedom
Execution on graphics processing units (GPUs)
r / mol/l
0 10 20 30
T / K
300
400
500
600
Dimethyl-hydrazin
Monomethyl- hydrazin
Hydrazin
Force fields for Hydrazine and two derivates
Simulation, this work
Experimental data from the literature +
Simulation, Gutowski et al. 2009
Hydrazine
Monomethyl-
hydrazine
Dimethyl-
hydrazine
e
e
e
Hi /
MP
a
0
500
1000
1500
N2
Ar
Hi /
MP
a
0
5000
10000
15000
20000
T / K
260 280 300
Hi /
MP
a
0
100
200
300
Stickstoff
Argon
Stickstoff
Argon
Stickstoff
Argon
Kohlenstoffmonoxid
Hydrazin
Monomethylhydrazin
Dimethylhydrazine
x,yH2O
/ mol/mol
0.0 0.2 0.4 0.6 0.8 1.0
T / K
370
380
390
VLE and gas solubility of
systems containing Hydrazine,
Monomethylhydrazine
and Dimethylhydrazine
Water + Hydrazine @ 1 bar
Nitrogen
Nitrogen
Nitrogen
e
e
e
Carbon monoxide
Elts et al., Fluid Phase Equilib. 322-323 (2012) 79
Simulation, this work
Experimental data (literature) +
Peng-Robinson EOS
Poster T37: Merker, Hsieh, Lin, Hasse, Vrabec:
Fluid phase equilibria for the oxidation of cyclohexane in carbon dioxide expanded
liquids from experiment, molecular simulation, Peng-Robinson EOS and COSMO-SAC
VLE and gas solubility of CO2-expanded liqiuds
Cyclohexane (C6H12)
6 LJ sites
Cyclohexanol
(C6H12O)
7 LJ sites +
3 point charges +
H
-
O
+
CH
Cyclohexanol (C6H10O)
7 LJ sites +
point dipole
Oxygen (O2)
2 LJ sites +
point quadrupole
Carbon dioxide (CO2)
3 LJ sites +
point quadrupole
0 5 10 15
devi
ation [%
]
-5
0
5
10
15
20
Poster T12: Dubberke, Vrabec:
Speed of sound of siloxanes as workings fluids in Organic Rankine Cycles
Speed of sound of Hexamethylsiloxane (MM)
365 K
pressure [MPa]
EOS: Colonna et al., 2006
xN2
/ mol/mol
0.00 0.02 0.04 0.06
p /
MP
a
0
4
8
12 30°C
70°C
90°C
126.85°C
50°C
0°C
-30°C-50°C
Acetone
Acetone in N2 and O2 under extreme conditions
Presentation Wed 10:40: Windmann, Köster, Vra.:
Study on vapor-liquid equilibria of nitrogen +
acetone and oxygen + acetone with a focus on the
extended critical region
Massively parallel molecular dynamics code: ls1
Flow
Nucleation
Identical force field types as with ms2
Additionally, Tersoff potential for solids
„Large“ systems, „long“ time scales
Concurrency in space, not in time
Scaling tests on Cray XE6 (Hermit)
Peak performance: 1.045 Pflops 1015 operations / s
Racks: 38 with 96 nodes each
Nodes: 3552
Cores: 113.664 (2 sockets each with 16 cores / node)
Processor: AMD Interlagos @ 2.3 GHz
#12
(November 2011)
Molekülzahl
105 106 107 108
Rechenzeit / s
10
100
1000
Computational effort ~ O(N1)
4.096 cores
1.000 time steps
Scaling of ls1 on Cray XE6 (Hermit)
Molecule number
Execution t
ime /
s
Octree load balancing strategy of ls1
Hierarchical subdivision of the simulation volume through recursive bisection
Choice of planes for bisection that lead to an equal load in the subvolumes
Designed for strongly inhomogeneous molecular systems
Capable to deal with rapidly changing inhomogeneity
Scenarios for scaling tests of ls1
Bulk Droplet Slab
Bulk: homogeneous liquid (Ethylene oxide)
Domain decomposition trivial
Slab: liquid slab surrounded by vapor in equilibrium (Argon)
Topology for domain decomposition simple
Droplet: liquid droplet surrounded by vapor in equilibrium (Argon)
Topology for domain decomposition more complex
Cores
102 103 104 105
Exe
cu
tio
n t
ime
/ s
10
100
1000 Bulk
Film
Tropfen
Strong Scaling
222 = 4.194.304 molecules
Droplet
Slab
1.000 time steps
Scaling of ls1 on Cray XE6 (Hermit)
Cores
102 103 104 105
Exe
cu
tio
n t
ime
/ s
10
100
1000
Bulk
Film
Tropfen
Strong scaling
226 = 67.108.864 molecules
Bulk
Scaling of ls1 on Cray XE6 (Hermit)
1.000 time steps
Droplet
Slab
mole fraction (N2)
0.0 0.2 0.4 0.6 0.8 1.0
pre
ssure
[M
Pa]
0
5
10
15
simulation
equation of state
experimental data
200 K
290 K
ξ = 0.974
VLE of Nitrogen + Ethane
Simulation
Peng-Robinson
Experiment (lit.)
Stoll et al., AIChE J. 49 (2003) 2187
Direct simulation of the LLE
• Mixture of 60 mol-% Nitrogen and 40 mol-% Ethane
• Identical molecular model as before
• 20,000 molecules
• Molecular dynamics with ls1
• Canonical ensemble (NVT)
• Initial configuration with randomly dispersed components
box length [nm]
0 2 4 6 8 10 12 14 16 18
mole
fra
ction
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
N2
C2H6
LLE of N2 + C2H6 after 48 ns
Temperature: 128 K
Pressure: 11.0 MPa
Average over
500,000 time steps
mole fraction of N2 [mol/mol]
0.0 0.2 0.4 0.6 0.8 1.0
tem
pe
ratu
re [
K]
115
120
125
130
135
p = 1.8 to 4.0 MPa,
depending on exp. data
LLE temperature dependence of N2 + C2H6
Simulation, this work
Experimental data, literature +
mole fraction of N2 [mol/mol]
0.0 0.2 0.4 0.6 0.8 1.0
pre
ssure
[M
Pa
]
0
5
10
15
20
LLE pressure dependence of N2 + C2H6
Simulation, this work
Experimental data, literature +
T = 127 to 129 K,
depending on exp. data
Poster T25:
Eckelsbach,
Vrabec:
Prediction of
liquid-liquid
equilibria of
nitrogen +
ethane with a
molecular model
that was
adjusted to
vapor-liquid
equilibria
Summary
The computational effort of classical force field methods scales
linearly with the molecule number
Classical force fields contain the thermodynamic properties adequately
Molecular dynamics simulations of inhomogeneous fluids
may efficiently use Petaflop machines
The spectrum of possible applications is very wide