1. Development of a Visualization Tool for the ARIES Systems Code
Stress work of others - myself just a small part.
Lane Carlson
ARIES-Pathways Project Meeting
UCSD May 19, 2010
19 May 2010

2. Systems code has evolved into a design space scanning tool
Rather than optimize about a specific design point, new approach scans a wide operating space for a range of possible design points.
It becomes necessary to visualize slopes - is it a steep optimization point with no leeway or at a shallow point with a relaxed constraint?
A larger design window may open when a constraint is slightly relaxed, with substantial improvement in COE.
Other times, moving away from the “optimized” point gives a more robust and credible design with minimal impact on COE.
START) Over the past few years, the systems code has evolved.
1)Constrained too tightly at optimal operating point, backed into a corner.
APPLICATIONS 1) Increased scanning capability and resolution with cluster.
3) Detailed hand and CAD analysis done for credibility.
Code is SELF CONSISTENT - it will fulfill its own equations but needs to be verified.
FLOW:
Large scan
Identify area of interest
Narrow down search
Specific point study
(From F. Najmabadi)
19 May 2010

3. Large databases can be processed
Have capability to parallel process the databases on a cluster with hundreds of nodes.
Princeton Plasma Physics (PPPL)
computer cluster:
200+ processors
Quad-core CPUs
Up to 16 GB RAM
1 gigabit ethernet
START) I mentioned that we might have 10^6-10^7 points to process.
CAN run on a laptop, just takes a long time.
Large systems scans are possible ( points)
Targeted systems scans around a region of interest
Operating point search and sensitivity scans, supported by detailed analysis
10^6 = 60 days on laptop vs 1 day with 20 nodes, or less with more nodes
2 GHz Core2 Duo laptop
AMD Quad-core node
~700 points/hr
~2000 points/hr
105 points =
142 hrs
= 50 hrs/node
106 points =
1428 hrs
= 500 hrs/node
10^6 = 60 days with laptop
vs.
1 day with 20 nodes
PPPL Cluster
19 May 2010

4. It is a challenge to visualize large data sets
Visualizing large datasets is a difficult task, almost an art
106 points overwhelm monitor real estate
“Lots of numbers don’t make sense to ‘low-bandwidth’ humans, but visualization can encode large amounts of data to gain insight.” - San Diego Super Computer Center
SDSCC Earthquake Simulation
NOAA (National Oceanic and Atmospheric Admin.) data-logging buoys
19 May 2010

5. NOAA Data Visualization
19 May 2010

6. More examples of visualizing large data sets
European Airspace Reboot:
During volcano activity (April 17, 2010)
World Data from Gapminder.org
Income per person vs. life expectancy
European Airspace Reboot:
After volcano activity (April 20, 2010)
19 May 2010

7. We are developing a visualization tool to utilize the scanning capability of the new systems code
VASST - Visual ARIES Systems Scanning Tool
Working to visualize the broad parameter space to extract meaningful data and uncover new relationships
Graphical user interface (GUI) permits 2D and 3D plots of any parameter
Purpose: to give the user more visual interaction and explorative power to bring to light new relationships
19 May 2010

8. (Visual ARIES Systems Scanning Tool)
VASST GUI Highlights
(Visual ARIES Systems Scanning Tool)
Number of points in database
Blanket database used
Auto-labeling
Pull-down menus for common parameters
Color bar scale
Constraint parameter set by user
Data cursor displays info on mouse-click
Correlation coefficient
Save plot as TIFF, JPEG, BMP, PNG…
19 May 2010

9. Example: Qdivinb vs COE, CC: B, constraint: B=8.5 T
SiC blanket
19 May 2010

10. Example: Qdivinb vs COE, CC: B, constraint: B=7.5 T
SiC blanket
19 May 2010

11. Example: Qdivinb vs COE, CC: B, constraint: B=7.0 T
SiC blanket
19 May 2010

12. Example: Qdivinb vs COE, CC: B, constraint: B=6.5 T
SiC blanket
19 May 2010

13. Example: Qdivinb vs COE, CC: B, constraint: B=6.0 T
SiC blanket
19 May 2010

14. Example: Qdivinb vs COE, CC: B, constraint: B=5.0 T
SiC blanket
19 May 2010

15. Extra: Pnelec (unrestricted) vs COE, CC: COE
SiC blanket
Possible attractive power plant designs in the 500 MW range
19 May 2010

16. Extra: B vs COE, CC: R
SiC blanket
19 May 2010

17. Extra: Btmax vs COE, CC: R
SiC blanket
19 May 2010

18. An additional visualization feature might include “linking and brushing” the data
Highlighting any parameter space would show real-time effect on other parameters
19 May 2010

19. Three important elements are required to operate VASST
A intuitive visualization tool
A capable, experienced user
In-depth chronicle of details   
param
COE
4 m 30
5 m 35
6 m 40
7 m 45 
19 May 2010

20. A chronicle/history is required for record keeping purposes
What input parameters were used?
What version of the systems code was used? (Subversion control)
What blanket was implemented?
What were the assumptions applied in the code?
What filters were implemented? (Pnetel, Qdiv, B, etc.)
What costing algorithms were used?
Every result/picture/graph should be backed up with specifics of its origin
19 May 2010

21. Revision control is necessary and helpful
Needful to control revisions to the code to keep track of changes made by multiple users.
Subversion (SVN) revision control software keeps the code centralized in a server repository.
Users can “check out” the code, modify it, then “commit” it back to the central server as the most recent updated version.
START) I mentioned that we might have 10^6-10^7 points to process.
CAN run on a laptop, just takes a long time.
Large systems scans are possible ( points)
Targeted systems scans around a region of interest
Operating point search and sensitivity scans, supported by detailed analysis
10^6 = 60 days on laptop vs 1 day with 20 nodes, or less with more nodes
19 May 2010

22. Clarification of assumptions
Btmax vs. SC current = ?
Three references are an order of magnitude apart.
START) I mentioned that we might have 10^6-10^7 points to process.
CAN run on a laptop, just takes a long time.
Large systems scans are possible ( points)
Targeted systems scans around a region of interest
Operating point search and sensitivity scans, supported by detailed analysis
10^6 = 60 days on laptop vs 1 day with 20 nodes, or less with more nodes
19 May 2010

23. Clarification of assumptions
From Jan 2009 ARIES meeting, Z.D.
Need clarification of specifics between DCLL and SiC blanket.
Any other assumptions that need concrete definitions? Basis for physics and engineering design?
Scaling factors from other designs?
START) I mentioned that we might have 10^6-10^7 points to process.
CAN run on a laptop, just takes a long time.
Large systems scans are possible ( points)
Targeted systems scans around a region of interest
Operating point search and sensitivity scans, supported by detailed analysis
10^6 = 60 days on laptop vs 1 day with 20 nodes, or less with more nodes
From paper, “An advanced computational…” by Z.D.
19 May 2010

24. We would like to fill in the operating space
Are there pertinent or interesting areas the ARIES team would like to look at?
- Increase Qdiv? Elongate plasma? More aggressive or relaxed B?
Comments, suggestions, improvements?
ARIES-AT physics
DCLL blanket
ARIES-AT physics
SiC blanket
Aggressive in physics
START) We have been talking about pushing the limits and scanning a design space, so how can we do this and what have we done so far?
Prior designs constrained us. For the first time we are able to move around in this space.
Abscissa (X), ordinate (Y)
Aggressiveness means tradeoff between risk and reward. High-tech and more risky or low-tech and safer.
(E.G.) ARIES-I, DCLL blanket: AGGRESSIVENESS is not just in the blanket, as shown here, but also in other systems such as higher magnetic materials and fields, higher thermal conversion systems, pushing limits of power on the divertor, plasma elongation capabilities, and so on.
Pushing the limits may be harder to achieve but we don’t want to be pushed into a tight design corner.
2) Use the systems code….the payoff is a fuller understanding of tokamak design.
ARIES-I physics
DCLL blanket
ARIES-I physics
SiC blanket
Aggressive in technology
19 May 2010

25. Summary
The systems code is operational and able to scan and process a large design space.
A first version of VASST GUI is operational and ready to look at pertinent system scans for the ARIES team.
Beginning chronicle of details and specifics of the different blanket modules.
Payoff of filling the operating space is a fuller, richer understanding of tokamak design.
Live VASST demo?
19 May 2010

26. Future work Re-examine the TF and PF coil j vs. B relationships.
Prior SC magnets may be too optimistic (3x)
- re-examine lower B fields for possible solutions.
Develop solutions to the power balancing within the limits of materials/coolants - critical to accessing smaller power plants.
After a broad scan, fill in the operating space of the four corners with sufficient resolution.
START) some areas that have surfaced recently in which we can use the systems code scanning ability are…
1) Revisit TF, PF coil j vs B relationship to make better projections in the future. We now have a design point for magnet coils from ITER, which we expect will be built.
2) High temp SC magnets look interesting but have some fundamental issues with fields perpendicular to the tape that degrade their performance. Therefore we may look for points that do not require very high fields at the magnets.
3) [Radiated power fraction = ( )]
19 May 2010

27. Extra Slides To discuss individually:
Rev number for costing algorithms?
2 blanket types: SiC and DCLL (C.K.)
DCLL
ΔFW = m
Δblkt = 0.50 m
ΔVV = 0.31 m
Δshld/skel = xIn(<Nw>/3.3) m
ηth ~ 42%, Ppump ~ 0.04xPfusion
SiC
ΔFW = 0.0 m
Δblkt = 0.35 m
ΔVV = 0.40 m
Δshld/skel = xIn(<Nw>/3.3) m
ηth ~ 55%, Ppump ~ 0.005xPfusion
START) some areas that have surfaced recently in which we can use the systems code scanning ability are…
1) Revisit TF, PF coil j vs B relationship to make better projections in the future. We now have a design point for magnet coils from ITER, which we expect will be built.
2) High temp SC magnets look interesting but have some fundamental issues with fields perpendicular to the tape that degrade their performance. Therefore we may look for points that do not require very high fields at the magnets.
3) [Radiated power fraction = ( )]
19 May 2010

28. ARIES systems code consists of modular building blocks
Systems code integrates physics, engineering, design, and costing.
Systems Code Analysis Flow
1. PHYSICS
Plasmas that satisfy power and particle balance
2. ENGINEERING FILTERS APPLIED
3. ENGINEERING & COSTING DETAILS
Power core, power flow, magnets, costing, COE
Systems code INTEGRATES and provides a detailed build with costs of components and COE.
PHYSICS: submit an input file (~25 parameters) specifying the range of constraints/parameters you want to vary and the resolution (finer takes longer)
PHYSICS FILTERS: to remove all improbable physics, P CD < Pheat, f bs < 1, Tau He/Tau e < 4.
May start out with millions of physics points, but after filtering out unreal solutions, may get hundreds to tens of thousands of possible design points.
ENG FILTERS:
1) 6-18 T, limited by material and plasma confinement requirements
2) 5-8 MW/m^2 for AT, LiPb, SiC, for CS, He-cooled
3) AT <6 MW/m^2
4) Near 1000 MW net electric power
DETAILS:
Blankets: blanket module allows different blankets to be tested: dual-coolant, lead-lithium (DCLL), silicon carbide (SiC), ARIES-AT = SiC faced with W, cooled w Pb-Li
ALSO, different blankets can be compared against each other. I.e. DCLL w/ and w/o manifold. Can compare the thermal conversion efficiencies of the blankets.
Costing includes direct and indirect costs, will explain more later.
Filters include:
Modules include:
Toroidal magnetic fields
Heat flux to divertor
Neutron wall load
Net electric power
Blankets
Geometry
Magnets
Power flow
Costing
DCLL
SiC
ARIES-AT
19 May 2010