1. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Executable Models of Fissile
Reactor Systems for Hardware
Simulation and Design
47th Summer Computer Simulation Conference
July 26-29, 2015
John Determan
Christy Day, Steven Klein, Marsha Roybal
Los Alamos National Laboratory
Advanced Nuclear Technology Group (NEN-2)
LA-UR-15-25136
1

2. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Program Supports Mo-99 Supply for Nuclear Medicine
2
Diagnostic Imaging
Single photon imaging remains the
workhorse of imaging worldwide. The
US performs 18 million procedures
annually for its patients; 99mTc is used
in 16 million of them
Current status of medical isotope supply:
• No domestic producer
• 60% US daily need produced in aging reactors that
use Highly Enriched Uranium (HEU)
• Reactors planned for shutdown in near future
• DOE / Industry working to develop new sources
99Mo → 99mTc + β− + νe (half life ~66 hours)
99mTc → 99Tc + γ (~6 hours half life)

3. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Profile of Current Producers
3
• >50 years old, multi-purpose
reactor
• 30 – 40% of world Mo-99 supply
• Owned by European Commission;
operated by Nuclear Research
and Consultancy Group
• HEU Targets
• Shutdown after 2015
• >50 years old, multi-
purpose reactor
• 30 – 40% of world Mo-
99 supply
• Owned and operated
by Atomic Energy of
Canada, Ltd.
• HEU Targets
• Shutdown 2018
• BR2, Belgium
• Osiris, France
• Safari-1, South Africa
• OPAL, Australia
These reactors produce ~95% of world Mo-99 Supply
• With exception of OPAL all are 40 or more years old
• Except OPAL and Safari all use HEU fuel and/or targets

4. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Aqueous Homogenous Reactor (AHR)
 Fissile material – capable of sustaining a nuclear fission chain reaction
 An AHR is a system where the fuel is in solution
 In an AHR the strong negative reactivity feedback due to temperature
and radiolytic gas void provides inherent stability to the system
 A variation is an accelerator driven system
• Accelerator provides source neutron flux
• Operates subcritical (keff < 1)
• Fissions still occurring so desired isotopes are being formed (6% of uranium
fissions result in Mo-99)
4

5. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Dynamic System Simulation (DSS) of AHR
5
 DESIRE
• Direct Executing Simulation In REal time, Granino A. Korn
• Used by LANL to model time evolution of a fissile solution system
• Verified by modeling historic AHR (SUPO, Silene, KEWB)
• Applied to new generation of fissile solution systems
 Represent all relevant components
• core geometry
• solution fuel
• cooling
• radiolytic gas
 Study operational mode performance
• start-up
• transition to steady-state
• response to core heating
• onset of radiolytic gas generation
• steady-state
 Estimate reaction to reactivity variations
• step increases to super prompt critical
• slow and rapid ramp insertions
• oscillations
 Examine system stability
Time Evolution Stability

6. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Tools for Hardware Simulation …
 Construct a
simulator for
system operations
• Front end
implemented in
National Instruments
LabVIEW
• Back end
implemented in MS
Visual C++
• Study human factors
issues in control
panel design, layout,
and operations
• Will be used for
operator training
6

7. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
…And Engineering Design
 Recast models into a designer’s toolkit
• Implemented in MS Visual Studio C# / C++
• Rapidly study design variations / options
7

8. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
DESIRE Model Conversion - Requirements
 Requirements
• Quick
• Accurately maintain semantics of DESIRE code
 Manual Translation vs. Automated Translation
• SUPO Model > 1200 lines of input
• Manual translation likely time consuming and error prone
• Automated conversion
— Expected to be highly accurate
— Largely a syntax conversion
— But not without its complexities
 At Least 2 SUPO Size Models
• Could spend several months manually converting 2 models
• Or, spend same time producing a system that would allow
conversion of future models as well
• Trade-off analysis favored automated conversion
Pros
Cons

9. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
DESIRE Model Conversion – DESIRE
9
 Features of DESIRE that differ from C++
• No declarations for most variables, real-valued by default
• Derivative defined directly as: d/dt <variable name> = <some expression>
• State variables stored in array
• Exponentiation represented with infix “^” operator
• All division is real valued
• Some system-defined functions unique: swtch(x) = 0 for x<=0, 1 for x>0
• Identifiers may be viewed as “constants” or “variables”
— Assigned only prior to DYNAMIC keyword: constant
— Assigned to after the DYNAMIC keyword: variable

10. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
DESIRE Model Conversion – C++
 C++ Resolution of issues
• Declaration of variables
— use assignments, d/dt statements, to categorize DESIRE identifiers
• constant, state variables, non-state variables
• Division
— Analyze statements for operands
— use casting on numerator to make all division real-valued
• Exponentiation
— Analyze statements for operands of “^”, convert to “pow” function
• System defined functions
— Implement things like “swtch”
— convert names, adjust parameter usage as necessary
 Complex expressions can have all of the above at several levels in a
single statement
10

11. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
DESIRE Model Conversion – Final Architecture
 DESIRE models execute in
general purpose integration
routine (engine) – converted
models should also
 C++ objects
• Base class defines the
integration engine
• Base class defines methods
that converted models
(subclasses) must implement
• Converter produces
polymorphic plug-in
subclasses
 System referred to as
SimApp
11
SimApp
DSS model = Dynamic System Simulation Model

12. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Numerical Integration Engine
 DESIRE is full featured
• 16 integration options
— Euler
— RK various orders
— fixed and variable step
— more
 SimApp currently implements 4th order Runge-Kutta (RK), fixed
time step
• Array holds state variables, derivative values of state variables
• Successive columns used for RK4 intermediate calculations
• Converted models define pointers to state array for all state variables
• Several inline functions defined for quick convenient access to state and
derivative data
• Code framework already established for expansion of integration options
12

13. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Engineering Design Interface – Goal
 Produce a tool more suited to engineering design than DESIRE
• DESIRE directly exposes all modeling detail and underlying physics; far more
than engineer needs
• Access to calculated results requires detailed knowledge of both model and
DESIRE
 Engineering Design Interface
• Facilitate design option studies for parameters of interest to design engineers
— change flow rates
— fuel concentrations
— wall material properties, etc.
• Facilitate analysis of operational scenarios
— Component failures
— Changes in reactivity (control rod actions)
— Coolant temperature and flow variations, etc.
• Stability analysis
13

14. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Engineering Design Interface – Features, Part 1
 Features
• Simulation Control
— Max Time
— Execute / Abort
— Save / Replay
• Initial Conditions
— customizable
tabs
— Save / reuse IC
sets
• Plot / Data
specifications
— Plot groups or All
Data
— Scaling
— Data display
options
• Time evolution
plots 14

15. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Engineering Design Interface – Features, Part 2
 Menu options
bring up alternate
displays in lower
quadrants
• Stability plots
— click plot to
show only that
plot
• Data table
— Amount of data
controlled by
slider
— Can go to CSV
file or screen
15

16. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Plots and Data Table May be Synchronized
 View menu
• ICs
• Data Table
 Data table
plots can be
synchronized
• Red line
shows sync
• arrow keys
move red line
and data
cursor
together
16

17. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Hardware Simulator - Goal
 Produce Hardware
Simulator
• Operator
instruction
• Control panel
human factors
17

18. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Hardware Simulator – C++ / C Interface Back End
 Same C++ numerical integration engine
 Same plug-in converted model
 Additional “extern C” interface for NI LabVIEW
• Runs “infinitely” instead of to a max time, so
— Init / Start / Step / Stop simulation controls
— Data Retrieval to drive display
— Demand interrupt to set specified model values at any time
• Coolant flow, temperature and rate, immediate or gradual change
• Reactivity
• Accelerator on / off / output level
• Much more
 Will have separate Instructor interface / student interface
• Instructor sets scenario
• Student must respond
18

19. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Comparison to DESIRE Results, SUPO Model, Part 1
 Several AHR operated
at LANL in past:
LOPO, HYPO,SUPO
 SUPO data used to
validate DESIRE
model, SimApp
validated against
DESIRE using SUPO
 Plots show essentially
identical results
• Identical modelling
inputs
• RK4 integration
implemented as close
as possible to DESIRE
• Parameters generally
agree within .01%
19
Power (kW) for SimApp and DESIRE.
Reactivity ($) for SimApp and DESIRE.
Ave. fuel temp. (°C) for SimApp and DESIRE.
Ave core void frac. for SimApp and DESIRE.

20. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Comparison to DESIRE Results, SUPO Model, Part 2
 Transients with “extreme” conditions
show greatest variance
(high rates of reactivity insertion,
high maximum reactivities)
• oscillations between core void fraction
and reactivity more pronounced in
SimApp than DESIRE
• Still, general agreement to within 0.1%
 SimApp will require smaller time
steps (0.0025) during “extreme”
transients, but DESIRE model (0.01 s)
does not
• SimApp does not allow user time step
control, but will restart calculation with
reduced time step when needed
20
Ave. core void frac. for SimApp and DESIRE
(final 400 s, detail)

21. Operated by Los Alamos National Security, LLC for the U.S. Department of Energy’s NNSA
Conclusion
 System for producing executable plug-in models reliable and efficient
 Converted models show good agreement with DESIRE models
 At this time
• Engineering Design Interface is in process of being transferred to commercial
partners
• Simulator Initial Beta being completed
 Future work
• Engineering Design Interface will be used by partners
• Simulator will be worked into a complete product
 Acknowledgement
• This work was performed on behalf of the National Nuclear Security Administration
(NNSA), Office of Material Management and Minimization (NA-23).
21