High performance computing for MHD

Report
High Performance Computing for MHD
Ramakanth Munipalli, P.-Y. Huang
HyPerComp Inc., Westlake Village, CA 91361
In collaboration with
S.Smolentsev, N.B.Morley, A.Ying, G.Pulugundla, M.Abdou,
UCLA
2nd EU-US DCLL Workshop, UCLA, November 15, 2014
Research supported by current and prior SBIR funding from DOE
Outline
1. HyPerComp Inc. – who are we?
Small company, located 30 miles NW of LA, estd. 1998,
Lengthy, fruitful collaboration with UCLA in numerical MHD
2. MHD – what have we done so far in fusion related MHD modeling?
3. Multiphysical extensions
Mass transport, corrosion, integrated multiphysical modeling
4. What are we working on now?
5. High performance computing – some tools and techniques
Some prospects and future directions
1. HyPerComp Inc. – Who are we?
HyPerComp develops high performance computing software in fluid
mechanics and electromagnetics
3 Recent Examples:
Very large scale CPU/GPU parallel
electromagnetics modeling
Liquid rocket combustion dynamics
Coupled fluid-structure-acoustics
modeling for rotorcraft
A Technology Portfolio
Computational Electromagnetics
RCS, SAR Imagery and range profiles,
Penetrable materials, Antennas, Optics
Magnetohydrodynamics
& Plasmadynamics
Flow Control,
Liquid metal MHD – nuclear fusion,
Combustion control
Computational Fluid Dynamics
Incompressible to Hypersonic flow,
Turbulent Combustion, Rotorcraft, Acoustics,
Morphing structures, Optimization
High Performance Multiphysical Computations
Very high order accurate solutions, CPU/GPU
based solvers, Reduced Basis Models
TEMPUS
HOME
HD Physics
HYCE
2. MHD – what have we done so far?
MHD
Top-level concern in fusion blanket studies
(pressure drop, corrosion, tritium transport, etc.)
Difficult problem to solve
No analytical solutions in all but the most elementary flows
Numerical solutions riddled with difficulties and uncertainties
HyPerComp Incompressible MHD solver for Arbitrary Geometry
HIMAG was developed by HyPerComp in a research partnership with UCLA
to model the flow of liquid metals in nuclear fusion reactor design. These
flows are characterized by very high magnetic field strength, complex
geometry and fluid-solid coupling via electric current and heat.
HIMAG is a pioneer in the reliable computation of such flows among both
commercial as well as research simulation software.
HIMAG: Technical Summary
 HIMAG is a parallel, unstructured mesh based MHD solver.
 High accuracy at high Hartmann numbers is maintained even on nonorthogonal meshes
 HIMAG can model single-phase as well as two-phase (free surface) flows
 Multiple conducting solid walls may be present in the computational
domain
 Graphical User Interfaces are provided for the full execution of HIMAG
 Heat transfer, natural convection, temperature dependent properties can
be modeled
Extensive validation and benchmarking has been performed for canonical
problems. Cases involving Ha > 1000 have never been
demonstrated on non-rectangular meshes prior to HIMAG
Governing Equations
 ui
 xi

t
Two phase fluid flow without MHD
 0,

  u i 
 xi
 0,
   2    1   2  H ( )
  ui 
t

  u i u j 
 xj
   2    1   2  H ( )
,
  ui 


 


 xi
 x j   x j 
 p

Two phase fluid flow with MHD, heat transfer
ui
t

 u i u j 
t
1   u i  J  B


 



 xi
  x i   x i 

    
1 p
viscous
T
t
 ui
T
xi

1
cp
   k  T  
Lorentz
J E  Q

g

gravity


  x  

 
surface
tension

  T  T ref g
  
buoyancy
Treatment of electromagnetic fields in liquid metal MHD
When the magnetic Reynolds number is low (Rem = μ0σLU << 1), induced magnetic
field is negligible. Applied magnetic field is the total magnetic field, and an electric potential




 
may be derived:
Ohm’s law: J       V  B 
E   
The potential is obtained from the condition that the current density is solenoidal

J  0

 
          V  B 
A more general treatment solves for the induced magnetic field:

B
t
  
  
 V   B  B    V 

1
2
 B

in the fluid,
J 

B

Electric current can flow across interfaces between media
solid
fluid
Appropriate simplifications (J=0, etc.), or,
Boundary conditions (normal current = 0) can be used
Numerical difficulties in computing high Ha MHD flows
1. The need to resolve and minimize numerical errors in Hartmann layers
(Thickness about 1/Ha)
2. The pace of convergence of Poisson equation solvers
(for Pressure, Electric potential, divergence of B)
3. Computationally intensive corrections for non-orthogonal meshes
4. Long periods of integration needed to account for flow development,
unsteady effects
5. Time taken to develop CAD to CFD mesh for high Ha problems
Flow enters a strong B-field
The high Hartmann number problem

As Ha = BL

increases, regions of
sharp variations in velocity and electric
current density appear in the flow.
Numerically, small inaccuracies in the
Hartmann layer are greatly amplified
The exacting needs of numerical MHD
FLOW
B
S id e la ye rs
~
1
Ha
1 / sqrt(Ha)
H a rtm a n n la ye rs
~
B
1
U(z)
Ha
j(y,z)
2h
d//≈Ha-1/2
Side layer
1 / Ha
dHa≈Ha-1
Hartmann layer
Verification against canonical benchmark problems
Fully developed flow at Ha = 10,000 in a duct
with square cross section – compared with the
exact analytical solution
Fully developed flow at Ha = 1,000 in a duct
with circular cross section
Natural Convection
A good match of Nusselt number with published data
has been observed. Second order accuracy has
been ascertained.
Ra
103
104
105
106
Ra = 103
Mesh
NuHIMAG
Nucomp
21x21
41x41
81x81
1.1227
1.1191
1.1181
1.118
21x21
41x41
81x81
2.3084
2.2611
2.2488
2.245
21x21
41x41
81x81
4.9370
4.6312
4.5490
4.522
21x21
41x41
81x81
161x161
10.661
9.4598
8.9885
8.8659
Ra = 104
Ra =
105
Ra = 106
8.829
Validation against experimental data: ALEX duct experiment (1987, ANL)
Circular duct
Ha=5800
Square duct
HIMAG: Some MHD specific numerics
Contact resistance
Wall functions
z
dH ~
S olid-fluid Interface
w ith contact resistance
1
Ha

u f  u ic 1  d Ha e
N
 Ha N

B
f
s
=0
 = 10
1
2
y
j

 
s   f  K J n
Coarse mesh in
Ha layers

Jump in potential at arbitrary
material interfaces can now be
captured
Robust modeling of strong natural convection
Newton-Krylov based schemes are used to perform matrix inversion in a upwind semi-implicit
procedure to stabilize the simulation of flow with strong natural convection (Gr = 10 9).
Flow in a 3-D channel
with MHD and heat transfer
(results in next chart)
Gr = 109 in a square cavity
Streamlines (left) and isotherms (right)
X
B
2
g
Ym
2a=20
cm
40
cm
A case study in the use of wall functions in solution acceleration
Flow Re = 10,000, Ha = 400, Gr = 107
Wall functions are used to model MHD flow in an insulating channel with dimensions similar to
DCLL. These functions are applied at all walls (iwall=10) or only at Hartmann walls (iwall=11)
Full MHD solution (left) and solution with wall functions (right)
Sample speedup results on 16 CPUs
Upward flow
Full solution iwall=0
g
Temperature
# cells
Speedup
299,440
1
Wall function iwall=10
70,080
19.18
Wall function iwall=11
162,336
6.2
Velocity contours
Comparison of full and wall function
solutions along centerline
DCLL concept and crucial MHD features
T o p P la te
FW
B a ck P la te A ssy
S iC
G rid P la te A ssy
B o tto m P la te
Full 3-D MHD (with natural convection) model of the DCLL
B
z
y
x
g
Flow enters from lower right, exits above
A low conductivity flow channel insert is present
Velocity profiles shown on right and pressure on left
3. Multiphysical studies
Fusion relevant liquid metal MHD includes a variety of multiphysical phenomena

Fluid, heat and mass transport

Natural convection

Steady and unsteady electromagnetic phenomena

Contact resistance (thermal and electric)

Ferromagnetic effects

Two phase flow, surface tension

Phase change (due to high heat flux, pressure variation, etc.)

Corrosion, electrochemistry at walls

Fluid-structure interaction
HIMAG: Free surface flow simulations
MTOR, experiment at UCLA
Liquid metal jet in a magnetic field
HIMAG: Free surface flow simulations – contd.
Plasma-liquid metal interaction in a magnetic field: DiMES
Plasma
Plasma-liquid interaction
Liquid metal
HIMAG uses the level set
method in unstructured meshes.
Method permits large
deformations of the free surface.
We are presently working on
massively parallel free surface
capture simulations with
scalable adaptive meshing
(w. RPI)
Mass Transport
 Tritium transport
We built an independent software named CATRIS from the basic data
structure of HIMAG, to focus on specific issues in mass transport.
 Corrosion
Some capabilities to simulate corrosion were added to CATRIS,
together with Lagrangian models for particulate transport
CATRIS (Corrosion And TRItium transport Solver)
Written as a new stand-alone system, CATRIS focuses on the following:
(a) the transport of tritium and its permeation through walls
(b) corrosion and deposition of iron contained within structural materials of the system.
Blanket Region
Individual components from outer region
Whole system modelling
CFD/MHD Solver
Thermal Hydraulics Code
Velocity and Temperature
CATRIS Code
Tritium Transport
Preprocessing
Grid Generation
Dissolution and diffusion
Properties
Transport in solids and fluids
Interfacial phenomena
Effect of He bubbles
Corrosion
Dissolution into PbLi
Surface layer effects
Nucleation
Transport of Fe particles
Deposition in cold regions
Numerical solvers
Advection/diffusion equation
Two-fluid model
Particle tracking
Visualization
Tritium transport and particle transport models in CATRIS
DCLL Geometry (not to scale)
Tritium concentration
in module computed for B=4T (Ha = 15 000), u=0.065m/s.
B
z
y
x
RAFS wall 5 mm
thick
2 mm
gap
y
2.0 m
2.26 m
Outflow
z
211 mm
FCI
SiC wall 5 mm thick
Inflow
207 mm
0.3 m
231 mm
A sample study to inject particles in an MHD flow, which migrate in response to
the gradient in an applied magnetic field. These particles will be produced at walls
using a corrosion BC and deposited likewise.
4. What are we working on now?
Current Research Objectives

Brand new software implementation of the induced magnetic field
formulation – adds ability to model high magnetic Reynolds number, strongly
unsteady flows

Improvement in time accuracy

Enhanced robustness and speed – better parallelization

Dramatically reduce simulation time for MHD flows in geometries of practical
interest – DCLL, etc.

Transition to general EM applications in materials processing
Induced magnetic field formulation
 1
 B 

   u  B        


t


 m 

B
• Boundary conditions for the induced magnetic field b:
 Approximate boundary condition:
b  B  B0
 b ||  b  b  n n  0

 b  n 

0

n
 Magnetic domain boundary condition
 b  0

 b 
0
  n
 Functional Decay based boundary conditions
1
b  b 
r
r – distance
 Integro-different boundary conditions
b  
so   b  0
b\\
bn
Case 1 – 3-D Lid-driven cavity with conducting
walls except top lid (Re=100, Ha=10, Cw=0.4)
U
B
a) Schematic view of 3-D lid-driven
cavity with conducting walls
(Blue area), Red – Liquid.
b) Velocity profile along x=0 and z=0 sections
Case 1 – Cavity with conducting walls - Continued
e) Comparison of velocity curves by
B-formulation with those by
potential solver (HIMAG).
f) Convergence history.
Case 2 – 3-D Lid-driven cavity with insulating walls
(Re=100, Ha=45)
U
B
a) Schematic view of 3-D liddriven cavity with insulating
walls: Red – Liquid.
b) Velocity profile along x=0.5 and y=0.5 sections
Case 2 – Cavity with insulating walls - Continued
Comparison of velocity w(x) by Bformulation with published data
Comparison of velocity u(z) by Bformulation with published data
5. High Performance Computing
Summary of our approach
Mathematical methods
Multigrid methods: Agglomeration, unnested premeshed scheme, algebraic multigrid
Hybrid meshes
Implicit schemes – time stepping, accuracy
CN, AB, SIRK schemes
SIMPLE scheme for steady flow
Local time stepping
Full matrix solvers – BICGSTAB on CPU/GPU
Interpolation procedures
Data storage: Non-orthogonal correction
GPU-based programming
Rapid prototyping
Canonical decomposition of DCLL geometry
User interfaces for inlet, fci, bend, etc.
Template for multigrid (3-D) – dir. agglomeration
Template for hybrid mesh generation blocking
Applications of analysis
EM coupling between neighboring channels
Fringing fields, self-consistent field formulations
Wall functions – insulating, perfectly conducting
Wall functions for fringing fields
Patched analytical – numerical solution
Combination of duct flow solutions
Poisson solver acceleration by sparse matrix storage and inversion
Cases
Poisson solver with
Neumann BCs
option
Run time
Log L2 norm
CG
iortho=1
95.7 s
-0.479
CG, K saved
iortho=1
57.9 s
-0.479
CG
iortho=2
221.9 s
-1.958
CG, K saved
iortho=2
138.9 s
-1.963
Cases
Hunt’s fully developed
channel flow
option
Run time
CG
iortho=1, nmhd=1
298 s
CG, K saved
iortho=1, nmhd=5
168 s
Option
Run time
iortho=2, nppe=1, nmhd=1
29783 s
iortho=2, nppe=5, nmhd=5
19633 s
Option
Run time
CG
iortho=1, nppe=1
19996 s
CG, K saved
iortho=1, nppe=5
13060 s
Cases
option
Run time
CG
iortho=1, nppe=1, nmhd=1
3205 s
CG, K saved
iortho=1, nppe=5, nmhd=5
1712 s
Cases
3-D circular duct Ha = 10, CG
Re = 10, cw = 0.1
CG, K saved
Cases
3-D rectangular duct
Ha = 0, Re = 15,250
3-D rectangular duct
Ha = 100, Re = 10,
cw = 0.1
The use of non-orthogonal meshes
Among the many benefits of the HIMAG approach has been the preservation of
accuracy on arbitrary mesh systems – making the calculation more efficient
Hybrid/unstructured meshes reduce number of mesh
points needed, by transitioning between regions of
different resolution requirements
“Template” driven mesh generation
HIMAG: A nested multigrid method
A sequence of unnested grids for multigrid Poisson solution, showing reduced convergence time
(above), automatic generation of a sequence of meshes from CAD input (below)
Some prospects and future directions
Summary
We have a number of ongoing software development activities which can serve
simulation needs in fusion:
Robust, comprehensive, self-consistent MHD physics modeling
CPU/GPU parallel computing
Highly scalable parallel mesh adaptation
Strengths in coupled MHD/heat/mass transfer analysis
(numerous existing physical and numerical models)
Integrated and customizable software solutions
Future Directions
EM toolkit for flow and materials processing
1. Combined calculation of fluid flow, heat transfer (radiative, convective), mass transfer
(including corrosion) and electromagnetics - applications in aerospace
propulsion, materials processing
2. Localized plasma models – thermal as well as weak ionization, extended to large
length scales as source terms (external flow control, plasma assisted
processing, radar analysis)
3. Two phase flow - models of free surfaces such as melt layers
4. Phase change - evaporation, melting, solidification, crystallization, etc.

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