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height="11.028472222222222in"}

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height="2.651388888888889in"}

Notice: This report was prepared as an account of work sponsored by an
agency of the United States Government. Neither the United States
Government nor any agency thereof, nor any of their employees, nor any
of their contractors, subcontractors, or their employees, makes any
warranty, express or implied, or assumes any legal liability or
responsibility for the accuracy, completeness, or usefulness of any
information, apparatus, product, or process disclosed, or represents
that its use would not infringe on privately owned rights. Reference
herein to any specific commercial product, process, or service by trade
name, trademark, manufacturer, or otherwise, does not necessarily
constitute or imply its endorsement, recommendation, or favoring by the
United States Government, any agency thereof, or any of their
contractors or subcontractors. The views and opinions expressed herein
do not necessarily state or reflect those of the United States
Government, any agency thereof, or any of their contractors.

Sandia is a multiprogram laboratory operated by Sandia Corporation, a
Lockheed

Martin Company, for the United States Department of Energy's National
Nuclear

Security Administration under contract DE-AC04-94AL85000.

**ON THE COVER:**

Dynamic void collapse in single crystal copper by dislocation emission.
Shown is a small section of a 2.13-billion atom molecular dynamics
simulation of a shock-compressed copper single crystal with a 0.41%
preexisting void density. The simulation was performed using the SPaSM
application running on BlueGene/L. Atoms in pristine fcc lattice sites
are not shown, atoms in hcp stacking faults are grey, and other atoms
(including surfaces and dislocation cores) are red. Untouched voids
ahead of the shock front are visible in the upper right, while the
complete collapse of voids leads to an array of planar stacking faults
(grey) bounded by partial dislocation loops (red) behind the shock
front. SPaSM is used to simulate many aspects of material phenomena,
including response of materials to shock waves and the growth of
instabilities and turbulence. The ASC Program uses results from such
simulations to better understand these phenomena for its programmatic
needs.

(Courtesy: Los Alamos National Laboratory.)

SAND 2006-7625P

Issued by Sandia National Laboratories for NNSA's Office of Advanced
Simulation & Computing, NA-114.

For more information, contact Njema Frazier njema.frazier@nnsa.doe.gov

+---------------------+------------------------------------------------+
| ![](media/ima       | Advanced\                                      |
| ge3.jpeg){width="1. | Simulation &\                                  |
| 5833333333333333in" | Computing\                                     |
| height="1.6         | ROADMAP                                        |
| 659722222222222in"} |                                                |
|                     | *National Nuclear Security through\            |
|                     | Leadership in Weapons Science*                 |
|                     |                                                |
|                     | **Dr. Dimitri F. Kusnezov, Director, NA-114**  |
|                     |                                                |
|                     | **Dr. Njema Frazier, NA-114**                  |
|                     |                                                |
|                     | **A Publication of the Office of\              |
|                     | Advanced Simulation & Computing,\              |
|                     | NNSA Defense Programs**                        |
+---------------------+------------------------------------------------+

ACKNOWLEDGMENTS

The *ASC Roadmap* is the third in a series of governing documents for
NNSA's Advanced Simulation and Computing Program (ASC). Like the first
two, *ASC Strategy: The Next Ten Years* and the *ASC Business Mode*l,
the *ASC Roadmap* has benefited from the dedicated efforts of more than
30 senior-level experts. Most importantly, the patience and thoughtful
guidance of NA-114, Office of Advanced Simulation and Computing, and the
support of the ASC Execs have made this effort a success. Our gratitude,
therefore, goes to all individuals involved and particularly to the
following:

  ---------------------------------------- ------------------------------
  **NA. 114**                              **Sandia National
                                           Laboratories**

  Dimitri Kusnezov                         *Paul Yarrington*

  ![](media/image4.jpeg){width="8.25in"    Jim Ang
  height="7.59375in"}Njema Frazier         

  Bob Meisner                              Sudip Dosanjh

  Thuc Hoang                               Art Hale

                                           Justine Johannes

  **ASC Execs**                            Michael McGlaun

  Art Hale (Sandia National Laboratories)  Marty Pilch

  Michel McCoy (Lawrence Livermore         Robert Thomas
  National Laboratory)                     

  James Peery (Los Alamos National         Timothy Trucano
  Laboratory)                              

                                           Reeta Garber

  **Lawrence Livermore National            Michael Townsend
  Laboratory**                             

  *Des Pilkington*                         Doug Prout (Technically Write
                                           for Sandia)

  *Michael Zika*                           

  *Kim Budil*                              **SAIC**

  Tom Adams                                Tina Macaluso

  Lynn Kissel                              Charlie Slocomb

  Jim Rathkopf                             

                                           

  **Los Alamos National Laboratory**       

  *Cheryl Wampler*                         

  Hans Ruppel                              

  Marv Alme                                

  Brad Beck                                

  Mark Chadwick                            

  Scott Doebling                           

  Rich Graham                              

  Doug Kothe                               
  ---------------------------------------- ------------------------------

**FOREWORD**

First and foremost, I believe that computational science and computer
simulation are the only means to integrate our national understanding of
weapons and their various behaviors and effects. Theory and experiment
are critical to developing component models and checking the veracity of
the computational predictions produced by those models, but only through
integrated, multiscale simulation can we explore the precise conditions
we want, at the scale we want, as thoroughly and quickly as needed. As
we move into a more complex global future, our need to respond will
hinge on our ability to simulate various scenarios and weapons issues.

An obvious question, then, is to ask to what extent leading-edge
scientific technology will be needed as we move into an era with a
smaller active stockpile, composed in significant numbers of a reliable
replacement warhead, which is supported by a modern production complex.
For the first time in the history of nuclear weapons, our nuclear
deterrent will rely upon devices that, though carefully compared with
the underground test data, have not been tested in their nuclear
regimes. I believe that sustaining the testing moratorium requires that
we transition to a point of sustainability at which our confidence in
science-based simulations exceeds our confidence in simulations
calibrated by underground test data.

Today's stockpile is overseen by seasoned experts, whose knowledge is
grounded firmly in our test experience and complemented by modern tools
and simulation. With the likelihood of maintaining weapons far into the
future, well beyond the loss of our first-hand understanding, we must
ask how we will train today's grade school children to certify and
assess in 2030. How will they develop the experience under weapons
conditions to assess the unknown issues or threats of the future, from
effects and outputs, to issues inherent in an older stockpile and a
collection of untested systems? Decisions today are based on not just
the test data, but also on the experience and expertise of trained
scientists and engineers that understand how design modifications and
seemingly innocuous changes can lead to surprising results.

I see the *Roadmap* as an essential blueprint for transformation. With
it, we can embark into this era of a reliable replacement warhead, aging
weapons, young designers, and new national security applications with a
plan for developing the transition to a sustainable scientific
competency for the nation.

> Dr. Dimitri Kusnezov,
>
> Director, NA-114

![](media/image5.jpeg){width="8.510416666666666in"
height="11.010416666666666in"}

EXECUTIVE SUMMARY

This *Roadmap* commits to goals that drive us to a future in which we
will be able to sustain credible assessment of systems in the stockpile
while maintaining the testing moratorium. Since the devices in the
stockpile change in their characteristics as they age, and since
refurbishments alter their properties, we cannot continue indefinitely
to base our assessments on calibrations tuned to the parameter space
defined by the as-designed test data. To be sustainable, stockpile
stewardship must be grounded in science-based simulations and data, and
the program must move to a point when science-based prediction overtakes
calibration and enables us to accurately assess the state of the devices
in the stockpile.

This direction follows from the program's *ASC Strategy: The Next Ten
Years*. The *Strategy* outlines the following agenda:

> The strategy for the next ten years...will set high-level directions
> and emphasize a deeper understanding of the underlying science, a
> continual replacement of the phenomenology in the weapon simulation
> codes by better theoretical models, and a quantification of their
> limitations.

For the strategy to be realized, the program has to determine the
high-level steps to be taken. Thus, the *ASC Strategy* and *Roadmap*
work in concert, with the *Strategy* providing broad guidance to the
weapons laboratories on scientific development areas required for
meeting mission commitments with greater confidence, and the *Roadmap*
providing details of the actual steps that must be taken to achieve
significantly greater confidence in the calculations. Both documents
support leadership in weapons science and the science-based simulation
required for the nation to meet a multitude of diverse needs---from
maintaining an aging stockpile (keeping systems from having to be pulled
out of the weapons arsenal), to supporting the broad range of Homeland
Security issues associated with national nuclear security (enabling
interdiction, supporting dismantlement of devices that make their way
onto our shores, and providing forensics and attribution of a nuclear
device), to avoiding technological surprise (examining what-if scenarios
to understand what options nuclear-nation states might be exploring).

This transformation to simulating a broader range of applications with
greater confidence is already happening. Take, for example, the Reliable
Replacement Warhead (RRW). The capabilities used in RRW development will
be the primary support for the Complex's transformation (i.e., Complex
2030) and the future stockpile. Modern machining, safe dismantlement,
and the development of further incarnations of the RRW will be made
possible by accurate simulations. The cost savings over trial and error
in manufacturing and experimental design and overly conservative
approaches to refurbishment will repay past investments many times over.

To support the aggressive timelines for transformation of the Complex,
the growing issues related to the aging stockpile, potential nuclear
threats to the nation, and the nation's commitment to maintaining a
capability-based nuclear deterrent into the future, the *Roadmap*
features four major components, or *focus areas*, to meet these
challenges and achieve the high-level *Strategy* goals:

• Address national security simulations needs;

• Establish a validated *predictive capability* for key physical
phenomena;

• Quantify and aggregate uncertainties in simulation tools;

• Provide mission-responsive computational environments.

These focus areas are the four key elements by which ASC will measure
progress, impact, and effectiveness. Each focus area has supporting
goals and targets with time lines to measure progress toward a
well-quantified predictive capability with computational environments to
support the larger-scale, intensive computations.

![](media/image6.jpeg){width="8.510416666666666in" height="9.3125in"}

1.0 SIMULATION AND THE CESSATION OF NUCLEAR WEAPON TESTING

For more than fifty years, the US nuclear program, spearheaded by the
test program in Nevada, satisfied the nation's nuclear weapons mission
needs. During this time, the Atomic Energy Commission (AEC) and its
eventual successor, the Department of Energy (DOE), maintained a
successful program of testing, surveillance, and simulation to ascertain
the behavior of nuclear weapons.

This paradigm shifted in 1992, when Congress initiated a one-year test
moratorium as part of the FY1993 Energy and Water Development
Appropriations Bill, which President Bush later signed into law[^1] on
October 2, 1992. From that point to this, the US Congress and each
administration have supported the extension of the moratorium
indefinitely.

In the years following the nuclear testing moratorium, the DOE Office of
Defense Programs faced several major challenges:

![](media/image7.jpeg){width="3.96875in"
height="2.6979166666666665in"}1. The population of weapons scientists
with direct experience of underground tests (UGTs) would inevitably
decrease as those scientists and engineers retired from the national
laboratories. Although they would be replaced by talented physicists and
engineers, the new weapons scientists would not be able to develop their
intuition and knowledge as their predecessors had from a cycle that
included calculation, testing, recalibration of the codes, and
calculation again.

2\. Code-development efforts would have to address the need for
three-dimensional representations of nuclear weapons phenomena. Earlier
codes were one and two dimensional and depended on assumed symmetries of
the weapon system. However, since devices are inherently three
dimensional and age in unforeseen ways, the codes would be required to
assess the three-dimensional time evolution of weapons behavior to
predict reliability and safety.

3\. More powerful computing systems would be needed to support the new
requirement to run three-dimensional simulations. Specifically, the
requirements called for systems many orders of magnitude more powerful
than those that existed in 1994.

These considerations led to the establishment of Accelerated Strategic
Computing Initiative (ASCI) in 1996 as an essential element of a
Science-Based Stockpile Stewardship (SBSS) Program. ASCI's main
objective was to provide high-fidelity, three-dimensional nuclear
weapons simulation and modeling capabilities on an "accelerated" time
line to meet the emerging needs of a stewardship program required to
sustain an effective deterrent in the absence of nuclear testing.

In 2000, ASCI transitioned from an initiative to a program, and it was
renamed the Advanced Simulation and Computing (ASC) Program. The
establishment of ASC affirmed simulation and modeling as key
decision-making tools and cemented their long-term role as integral
components of the Stockpile Stewardship Program (SSP).

The SSP---with the ASC Program:

• Allows the US to continue an underground nuclear test moratorium and
still maintain a reliable nuclear weapons stockpile.

• Ensures that all aspects of nuclear weapons stockpile operations are
safe and secure--- from design and engineering through dismantlement.

• Generates a large return on investment by providing cost-effective,
simulation-based solutions (without testing) to issues facing the
nuclear weapons stockpile---resolving significant finding investigations
(SFIs), conducting annual assessments for certification, enabling
stockpile lifetime extension programs, and responding to emerging
requirements, such as the Reliable Replacement Warhead (RRW).

Lastly, as the US maintains its moratorium on underground nuclear tests,
the Complex cannot continue to base its simulation and modeling efforts
solely on data that are increasingly removed from the reality of the
aged-weapons' performance. Previously, both the limited computational
tools and the near-term commitments to support the stockpile
necessitated this approach. Now, however, we have a development path for
the needed software and hardware tools to move towards a quantified
predictive capability (Figure 1). This *Roadmap* is designed to focus
the ASC Program's efforts over the next decade on providing new levels
of predictive capability to the SSP. It defines focus areas and
supporting goals and targets required to achieve predictive capability
in modeling and simulation, and it articulates a sequential,
priority-based approach to achieving a new level of fidelity, adding
confidence to SSP decisions and supporting a capability-based nuclear
deterrent into the future.

![](media/image8.jpeg){width="7.4847222222222225in"
height="6.713888888888889in"}

Figure 1---Near-term weapons support and long-term science base.

2.0 THE CASE FOR FUTURE SUSTAINABILITY

Computer simulation is, and will continue to be, the only means to
responsively address emerging issues related to systems under nuclear
conditions. This continued capability is crucial, then, to the nation's
commitment not to conduct underground nuclear tests. We are following
two paths that allow us to maintain the testing moratorium: the
traditional path of fitting our computer models to underground test data
and performing simulations in regimes that are minimally removed from
the applicable parameter space, and the rigorous, science-based path
intended to address a diverse portfolio of current and future nuclear
applications.

As Figure 1 illustrates, aging and refurbishment push nuclear weapons
behavior into an area where the uncertainty associated with traditional
approaches becomes progressively larger. To credibly address this space
and predict performance further from the as-tested configurations, we
must create modern physical models with capabilities enabling confident
calculation in these new and more applicable regimes.

2.1 NEAR TERM: THE LIFE EXTENSION PROGRAMS

To meet the needs of the SSP in the near term, ASC has aggressively
pushed computational capabilities and enhanced simulation tools. By
using test data to calibrate the major approximations (the "knobs") in
the models, code developers and designers have built effective computer
representations to probe scenarios at and near the area of our test
experience. The process of calibration allowed for credible
interpolation between different nuclear tests and for small
extrapolations to untested conditions. However, this same process
conceals the unknown science and engineering issues---since it allows
for compensating errors in various approximations that can mask reality.

The traditional approach contains a number of severe limitations:

• Confidence in our predictions decreases as the weapons systems change
because of aging and refurbishment. Put another way, the uncertainty
increases, as illustrated in Figure 1(b)-(c), as the test data become
less and less relevant to the aging and refurbished weapons we maintain.
As a consequence, we are increasingly less confident that our
calibrations to match the underground nuclear data provide accurate
representations of nuclear behavior.

• We cannot provide credible error bars for our predictions if the
simulations are adjusted by design to match the data against which we
are attempting to quantify the uncertainties.

As an interim approach, during the transition between the traditional
and scientifically grounded paths, we have succeeded in reducing the
rate at which confidence decreases by increasing dimensionality of the
weapons codes from 1-D and 2-D to 3-D; performing much higher-resolution
simulations to surface engineering and physics details that were
previously not discernible; and speeding up the codes through faster
computers and better algorithms. The cumulative effect of these actions
allows a clearer understanding of our interpolations and extrapolations.
However, in the long term, this approach will continue to lead to
*reduced confidence with time* as illustrated in Figure 1(b)-(c), or
equivalently increased uncertainty, because the underlying approximation
is still calibrated to the test data.

2.2 long TerM: FUndAMenTAl SCIenCe-BASed repreSenTATIonS oF weAponS
BehAVIor

Reliance on simulations calibrated to the test data is not feasible
indefinitely. Inevitably, issues will arise that were neither
anticipated nor explored in the days of UGT. It is clear that a parallel
long-term activity, focused on better scientific understanding and
well-grounded approximations that enable the computer models to provide
improved confidence with time, is critical. By systematically attacking
the major scientific hurdles, the program will gradually remove the need
to calibrate to the test base. The RRW effort provides significant
motivation to shift the emphasis from the near-term approach that we
have been following, Figure 1(b)-(c), to a sustainable effort based on
solid science and engineering, Figure 1(d)-(f).

There are several clear advantages to the replacement of "knobs" with
credible scientific models:

• Confidence in our predictions will improve with time.

• The nuclear test base will be used to confirm our simulation
predictions, rather than as a calibration point.

• Simulation will be a robust, responsive, and versatile tool in which
uncertainty bounds can accompany predictions.

2.3 The TrAnSITIon To SCIenCe-BASed SIMUlATIonS

The *Roadmap* time line and focus areas are driven by the need to ensure
that the transformed stockpile of 2030 poses a credible nuclear
deterrent. To this end, we are emphasizing long-term science and the
removal of the "knobs." This is illustrated notionally by the crossover
point of the two uncertainty curves shown in Figure 1(f). This is the
point in time when our confidence in approximations based on scientific
understanding exceeds the confidence we have from test base calibration.
We refer to this as "The Point of Sustainability"---when our decisions
are based on science-based computation not codes calibrated to past
nuclear tests. Reaching this point will allow the SSP to sustain a
credible nuclear deterrent because it will rely upon a simulation
capability that is science based and relevant to the regimes of crucial
importance. Clearly, if we delay, the blue envelope of uncertainty in
Figure 1(d)-(f) will grow, and the transition to the science-based path
(at the point of crossing) will be pushed into the future. The *ASC
Roadmap* defines the actions we plan to take to enable making this
transition achievable in time to ensure that the transformed stockpile
is a credible nuclear deterrent.

3.0 pATh To predICTIVe CApABIlITY[^2][^3]

As NNSA undergoes a transformation towards a responsive nuclear weapons
infrastructure---as called for in the Nuclear Posture
Review^2^---simulation is recognized as a key enabling technology for
this transformation. An increasing emphasis on reliability, surety, and
enhanced manufacturability places heavy demands on the ASC simulation
tools. The stockpile of tomorrow will contain Legacy weapons,
refurbished Legacy weapons, and reserves from which either parts or
entire weapons can be used for augmentation of the active
stockpile---including systems with enhanced surety features, such as the
RRW.

The *ASC Roadmap* describes the four focus areas deemed essential for
achieving the mission and strategic goals of the program:

1\. *Address national security simulation needs* by delivering the
capability to support the current and future SSP mission and by
retaining the flexibility and robustness to respond to unanticipated
events.

2\. *Establish a validated predictive capability* by investigating key
physical phenomena, developing a fundamental understanding of the
underlying physical processes, deploying enhanced science-based models
to reduce uncertainties, and reducing the reliance on ad hoc^3^ models.

3\. *Quantify and aggregate the uncertainties in simulation tools*
associated with material data, physics models, algorithm choices, and
numerical discretization inherent in simulation of complex phenomena,
and thereby increase confidence in simulations.

4\. *Provide mission-responsive computational environments* that meet
stockpile stewardship needs and achieve the scale required for
predictive capability through a balanced portfolio of capacity,
capability, and advanced computing, as well as greater integration of
the user environment and improved cost effectiveness.

As delineated above, the focus areas are the broad descriptions of the
high-level, high-priority activities for the program. Each focus area is
accompanied by goals and targets that span the next decade. The *goals*
are designed to inspire longer term innovations aimed at making
challenging, or "stretch," outcomes achievable at some future time.
While it might be hoped to achieve a stretch goal either partially or
fully within a defined time frame, the timing of the achievement of the
stretch goal cannot be guaranteed---it can only be striven for through
focused programmatic effort. The targets are clear, quantifiable,
challenging deliverables against which we can measure the progress
towards *Roadmap* goals and achievement of the focus area objectives.
These goals and targets are described in more detail below, with
out-year targets, in particular, being represented in the ASC Targets
insert.

FoCUS AreA 1. AddreSS nATIonAl SeCUrITY SIMUlATIon needS

This focus area centers on the simulation tools required to support the
current and future SSP mission, in particular to assess and maintain the
existing and future nuclear deterrent---including the RRW---in the
absence of UGT.

It is crucial that the ASC Program possess computational flexibility and
robustness to respond to unanticipated future needs. ASC simulation
tools will continue to support the resolution of SFIs and enable
Stockpile Life Extension Programs (SLEPs) for the stockpile. The
activities associated with each goal below will improve confidence in
the ability to extend beyond the current design base. This ability is
essential for certification of the future stockpile as it ages and
continues to depart from the UGT database. Additionally, ASC will
develop its capabilities for application to broader national security
applications in collaboration with other government agencies such as the
Department of Defense (DoD), Department of Homeland Security (DHS), and
Defense Threat Reduction Agency (DTRA). These activities will also
increase the robustness and flexibility of the simulation tools and
demonstrate an ability to respond to evolving national security needs.

There are four goals within this focus area.

1.1 delIVer SIMUlATIon CApABIlITY For nUCleAr weAponS needS (2007--2009)

In conjunction with Directed Stockpile Work (DSW) and the Campaigns, ASC
will identify and deliver the physics, engineering, and computational
capabilities to meet current and anticipated SSP needs. Particular
emphasis will be given to delivering the capabilities required to
establish baselines using ASC tools for all weapon systems, including
the RRW, by 2009.

1.2 delIVer SIMUlATIon TeChnologY For BroAder nATIonAl SeCUrITY needS
(2007--2012)

In addition to meeting SSP needs, ASC will demonstrate the ability to
apply ASC stockpile simulation technology and resources to broader
national security challenges (e.g., nonproliferation and threat
reduction). Thrust areas will be identified and mutually beneficial
partnerships established with external organizations to help address
their challenges. Use of ASC simulation capabilities in collaboration
with partner organizations to address several key national security
applications will be made by 2012.

1.3 InVeSTIgATe And UnderSTAnd oFF-norMAl SYSTeM perForMAnCe And
FAIlUre/AnoMAlY ISSUeS In The TeST dATABASe (2008--2013)

In a collaborative effort, DSW, Campaigns, and ASC will analyze
off-normal system performance by simulating selected tests using
best-practice models and methodologies. Based on these analyses,
improvements to physics models will be investigated, and evidence will
be gathered to identify unresolved physical processes.

1.4 delIVer enhAnCed SIMUlATIon CApABIlITY For FUTUre nUCleAr weAponS
needS (2010--2015)

Quantification of Margins and Uncertainties (QMU) assessments,
discoveries from the Campaigns, and developments from other ASC
activities will determine the physics, engineering, and computational
requirements and the necessary simulation tools that need to be
developed to increase confidence in stockpile weapons assessment,
certification, SLEP evaluation, and SFI closures. This enhanced
predictive capability will be verified and validated to the level needed
to address evolving DSW requirements and SSP issues.

![](media/image9.jpeg){width="3.5in"
height="2.6145833333333335in"}TArgeTS For FoCUS AreA 1

-   2008: National code strategy

-   2009: Modular physics and engineering packages for national weapons
    codes

-   2012: Tested capability to address emerging threats, effects, and
    attribution

-   2013: 50% improvement in setup-to-solution time for SFI simulations
    (with respect to 2007)

-   2014: Full-system engineering and physics simulation capability

-   2016: Capability to certify fire safety for an unfielded weapon

-   2019: 50% improvement in setup-to-solution time for SFI simulations
    (with respect to 2013)

FoCUS AreA 2. eSTABlISh A VAlIdATed predICTIVe CApABIlITY\
For KeY phYSICAl phenoMenA[^4][^5]

To reach the goal of predictive capability in simulation/analysis codes,
the SSP must establish an experimentally validated theoretical
understanding of the physical processes that impact the performance of
nuclear weapons. This effort begins by identifying key physical
phenomena from which physics and engineering models are developed,
progresses through simulation verification and validation, and concludes
with the delivery of a predictive capability to be adopted in the ASC
integrated performance codes. Delivery of this capability is therefore
the shared responsibility of the ASC Program and the Campaigns to
perform the required scientific discovery and DSW, and the verification
and validation.

This focus area has three major aims: (1) discover the underlying
physical phenomena behind the models that have been calibrated to
experimental results, that is, the ad hoc models; (2) replace the ad hoc
models with computationally effective, physics-based models as
alternatives; (3) reduce the uncertainty in any physics-based model or
database to the degree that is needed by QMU and validation studies.

To ensure that these aims are met, ASC will exploit the most recent
simulation capabilities and work closely with the Campaigns as they use
their ever-improving suite of experimental capabilities and
data-acquisition techniques. Maximum progress will be achieved in these
investigations through focused, well-integrated, coordinated activities.
ASC will establish a Center to coordinate activities across ASC
(laboratories and *Alliance Centers*^4^), with the Campaigns, and with
external collaborators. This Center will employ a broad variety of
capabilities, including theoretical studies and direct numerical
simulation (DNS),^5^ to explore isolated physical processes,
experimental data analysis to validate models, and performance and
analysis codes to perform integrated simulations. Ultimately, predictive
capability is achieved through incorporating improved physics and
engineering models in the integrated ASC codes and validating these
simulations against relevant above-ground experiments and nuclear test
data.

There are four goals in this focus area.

2.1 delIVer A progrAM plAn And eSTABlISh A CollABorATIVe CenTer To
AChIeVe predICTIVe phYSICS CApABIlITY (2007--2008)

By 2008, ASC will collaborate with the Campaigns and deliver a national
program plan defining the path to an enhanced predictive simulation
capability. Included will be a prioritized list of the major
uncertainties that need to be reduced and a list of the ad hoc models
that need to be replaced. Additionally, candidate physical processes
will be identified that may explain and allow the removal of the ad hoc
models. A center focused on predictive capability will be established to
ensure coordination and collaboration among the participants, including
the relationship with the Campaigns and external collaborators. Roles
and responsibilities for all participants will be defined along with
proposals for the scientific work that will be needed. In 2007, ASC will
support efforts with the Thermonuclear Burn Initiative (TBI)---a pilot
for the Virtual Collaborative Center model---to focus on one of the
critical hurdles to predictive capability.

2.2 ApplY TheorY, SIMUlATIonS, eXperIMenTAl dATA, And InTerIM ModelS To
ConFIrM doMInAnT phYSICAl phenoMenA (2008--2009)

As efforts progress toward an enhanced predictive capability, ASC will
deploy improved interim models with theoretical and experimental
backing. Detailed assessment of the candidate physical processes using
numerical, theoretical, and experimental means will have commenced and
will inform the improvements in the interim models. These studies,
supported by peer-review, will identify a subset of the candidate
physical processes currently represented by ad hoc models, deploy
interim improvements to reduce reliance on ad hoc models, and identify
essential experiments to confirm these conjectures.

2**.3 deMonSTrATe IMproVed phYSICS UnderSTAndIng BASed on releVAnT
eXperIMenTAl reSUlTS (2009--2013)**

In collaboration with the Campaigns, experimental programs will be
proposed to validate the representative models for physical processes
that describe the key physical phenomena. The conclusion of this
activity will be to confirm which candidate processes are eligible to
replace the old ad hoc models and the quantification of the extent to
which they have reduced uncertainty. Progress depends critically on
availability and alignment of experimental priorities at the major
experimental facilities (e.g., Dual Axis Radiographic Hydrodynamic Test
Facility \[DARHT\], Z-Pinch Refurbishment Project \[Z-R\], National
Ignition Facility \[NIF\]).

2.4 deVelop And deploY VAlIdATed predICTIVe ModelS For KeY phYSICAl
phenoMenA (2010--2015)

Accurate, effective numerical methods will be derived, and scalable
algorithms will be implemented to represent the new science-based models
in the integrated codes.

Model parameters and physical data will be extracted from the supporting
theory, simulation, or experiment. The integrated codes will be
validated against relevant experiments and then be delivered to DSW to
be used on stockpile problems.

TArgeTS For FoCUS AreA 2

-   ![](media/image10.jpeg){width="3.5in"
    height="2.6145833333333335in"}2007: Launch Thermonuclear Burn
    Initiative collaboration

-   2008: Realistic plutonium aging simulations

-   2009: Science-based replacement for Knob (ad hoc model) #1

-   2010: Science-based models for neutron tube simulations

-   2012: Validated science-based replacement for Knob (ad hoc model) #2

-   2014: Science-based models for fire-excitation simulations

-   2015: NIF-validated simulations supporting replacement of Knob #3

-   2018: Predictive model for Knob (ad hoc model) #4

FoCUS AreA 3. QUAnTIFY And AggregATe UnCerTAInTIeS In SIMUlATIon ToolS

The aims of this focus area are (1) to establish a comprehensive
methodology for quantifying and aggregating the uncertainty in weapons
calculations and (2) to establish and maintain a prioritized list of
model and parameter uncertainties in these simulations. To achieve these
aims, it is important to identify the approximations, assumptions, and
adjustments in weapon calculations. The subsequent steps will be to
assess the sensitivity of the simulation to these factors and then to
quantify their uncertainty from both physical and numerical sources.
Both will require verification problems of increasing physical and
geometric complexity and the identification of additional experiments to
validate the codes and assess the uncertainty of specific models.
Identifying the priority of these models and parameters will help guide
the uncertainty reduction efforts in Focus Area 2.

Simple procedures are available for assessing calculational sensitivity
to individual parameters, although these procedures can be
computationally intensive. The SSP requires an ability to assess the
overall calculational uncertainty by aggregating the effect of the
uncertainties in all aspects of the calculation. It is vital, therefore,
not only to gain an appreciation for the uncertainties in each part of
the calculations, but also to identify, assess, and validate procedures
for aggregating these uncertainties. These methodologies will be
demonstrated by application to the stockpile and utilization in QMU
assessments in design processes.

This focus area has three goals.

3.1 eSTABlISh And prIorITIZe The pArAMeTerS MATrIX (2007--2008)

ASC will establish a detailed, hierarchical list of the major parameters
and modeling options introduced in weapons calculations---along with
their feasible ranges and distributions. A tri-lab status-ranking
mechanism for physics and engineering codes based on sensitivity
(likelihood) and consequence (impact) will be defined with an initial
status for each list item. This peer-reviewed, prioritized list will
then define the priorities for future work in reducing the uncertainties
in ASC simulations.

3.2 eSTABlISh nATIonAl And CollABorATIVe ForUMS To deVelop UnCerTAInTY
AggregATIon MeThodologIeS And BenChMArKS (2008--2009)

In addition to identifying sources of uncertainties, ASC will establish
national and collaborative forums to develop methodologies and
benchmarks required for verification, validation, and quantification and
aggregation of uncertainty in weapons simulations. In particular,
quantification is needed for the effects of mesh resolution, numerical
discretization, material data uncertainties, physics models, and
algorithmic approximations on calculations. Advances will also be made
on methods for combining fundamental data and model uncertainties with
integral uncertainties obtained in more integrated experiments.
Uncertainty quantification and aggregation during a calculation is an
evolving science, and several candidate methodologies need to be
developed and assessed on relevant problems, with leading candidates
selected for further development and application.

3.3 delIVer UnCerTAInTY AggregATIon For QMU ApplICATIonS (2008--2014)

By 2014, ASC will deliver an uncertainty aggregation process for
application by DSW. This will include uncertainties for all relevant
material properties data, numerical discretizations, physics models, and
algorithms. Algorithms and frameworks required for uncertainty
quantification and aggregation will be defined and applied to targeted
stockpile calculations in support of QMU-based stockpile activities.

TArgeTS For FoCUS AreA 3

-   2008: National verification & validation strategy

-   ![](media/image11.jpeg){width="3.4in"
    height="2.2881944444444446in"}2008: Assessment of major simulation
    uncertainties

-   2009: Shared weapons physical databases

-   2010: Uncertainty Quantification (UQ) methodology for QMU

-   2012: 20% reduction in overall prediction error bars (with respect
    to 2006)

-   2013: Re-assessment of major simulation uncertainties

-   2014: Demonstrated uncertainty aggregation for QMU

-   2017: 20% reduction in overall prediction error bars (with respect
    to 2012)

FoCUS AreA 4. proVIde MISSIon-reSponSIVe CoMpUTATIonAl
enVIronMenTS[^6][^7][^8]

The objective of this focus area is to provide the computational
environments for carrying out the SSP mission. Broadly, this includes
providing the appropriate balance of capacity, capability, and advanced
computing resources to match the needs of the weapons program. Thus,
efforts will focus on improving the usability of the computational
environment, improving the cost performance of both software and
hardware, and making strategic investments so that ASC can continue to
meet the requirements of the SSP at an acceptable cost.

Both the complex and diverse demands that ASC performance and analysis
codes place on the computational environment and the scale of the
required simulations have positioned the ASC Program far in advance of
the mainstream high-performance computing community. To achieve
predictive capability goals, the ASC Program must continue to invest in,
and influence, the evolution of computational environments. This will
require radical innovation, tempered by the understanding that computing
environments must be stable and should not require applications to be
substantially rewritten or reinvented without realizing significant
returns.

Immediate priorities include moving toward a more standard user
environment, deploying more capacity^6^ platforms, and developing
petascale^7^ computing to support the scientific investigations needed
to achieve predictive capability and to perform aggregated uncertainty
quantification studies.

In accordance with the Complex 2030 vision, ASC will look to operate
capability computing as a national user facility, accessible
complex-wide, to address the most challenging and pertinent stockpile
stewardship issues. Partnering with computer vendors to develop advanced
architectures that show promise to meet the future computing needs of
the Complex, developing a common user environment, and reducing the
footprint of weapons program capability computing to two sites.

This focus area has three goals.

4.1 deploY CoMpUTATIonAl enVIronMenTS For UnCerTAInTY QUAnTIFICATIon
(UQ) AnAlYSeS (2007--2008)

Extensive Verification & Validation (V&V) and UQ simulations impose new
requirements on the tools, infrastructure, and computing platforms. In
collaboration with DSW and the Campaigns, ASC will gather requirements,
identify solutions, and deliver the computational environments needed to
meet deliverables in the 2009 time frame. Particular attention will be
given to the balance between capacity and capability^8^ computing. An
important development will be improving the usability of capacity
computational environments through common tools and interfaces.
Productivity will be enhanced by reducing time to solution through
increased performance, improved turnaround time, decreased problem and
grid setup time, and enhanced problem analysis.

4.2 deploY CoMpUTATIonAl enVIronMenTS And USer FACIlITIeS For weApon
SCIenCe STUdIeS And oTher CApABIlITY CoMpUTIng needS (2008-2012)

The computing resources needed to support the *ASC Roadmap* focus areas,
as well as DSW and Campaign deliverables, in the 2013--2015 time frame
will be identified and delivered. (In 2005, a national ASC study, in
support of an NNSA Defense Programs Level 1 Milestone, established that
a number of weapon science studies require a petascale computing
environment.) The demands on these architectures will be used to drive
leading-edge hardware and software technology with progress in Advanced
Systems likely to be required. Algorithms, tools, and system software
will be developed to increase scalability, manage petascale data sets,
and take full advantage of evolving Advanced Systems technologies. ASC
will continue to engage in partnerships with advanced architecture
vendors to achieve higher efficiency and improve balance across the
range of hardware components. Application performance analysis and
modeling will be applied to identify gaps, guide the path for algorithm
development, and determine the desired architectural balance for future
computing systems.

Additionally, a user facility model will be implemented to ensure that
the most challenging problems of the Complex receive essential computing
services. Implementing the Capability Computing Campaign (CCC) user
model will serve as the foundation for computing resource delivery
across the Complex. The User Facility Model will be cost-effective
remote computing consistent with the Complex 2030 transformation plan.

4.3 deploY CoMpUTATIonAl enVIronMenTS For enhAnCed predICTIVe CApABIlITY
In 2015 (2011--2014)

ASC will deploy the computational environment necessary to perform the
most complex and predictive weapon simulations ever achieved using
integrated ASC codes. ASC will collaborate with industrial, academic,
and government partners to build on the "weapons science" computational
environments to deliver balanced computing resources supporting program
deliverables in the 2015 time frame. Supporting infrastructure will be
implemented for moving, managing, storing, and analyzing data generated
at the petascale. System software, solvers, algorithms, and enabling
technology will be developed to enhance user productivity and achieve
the required scalability. Work in this time frame will establish the
technological foundation to build toward exascale computing
environments, which predictive capability may demand.

![](media/image12.jpeg){width="3.25in" height="2.15625in"}TArgeTS For
FoCUS AreA 4

-   2007: Initiate new National User Facility model for capability
    supercomputing

-   2008: Seamless user environments for capacity computing

-   2009: Petascale computing

-   2013: Seamless user environments for capability computing

-   2016: 100x petascale computing

-   2018: Exascale computing

![](media/image13.jpeg){width="8.5in" height="11.010416666666666in"}

4.0 ConClUSIon

The *ASC Roadmap* will serve as (1) a guidance document; (2) an input to
program plans; (3) an organizing tool for defining progress, and (4) a
basis for judging the evolution of simulation capabilities. Most
importantly, it describes---for both internal and external
stakeholders---the future direction of the ASC Program for the next
decade and beyond.

This document represents a significant development not only for the ASC
Program, but also for Defense Programs and NNSA. The three laboratories
have collaborated on a unified strategy to meet the programmatic
mission. We expect this *Roadmap* to deliver on its full potential as it
is becomes more tightly integrated with the Campaigns and DSW. Moreover,
it will drive changes to organizational behavior and business processes
within ASC and influence change in other programs.

Finally, while the next steps involve distribution and discussion of the
*Roadmap* and development of ASC program plans and implementation plans
that are consistent with the needs defined in the *Roadmap*, this
document will continue to evolve. Even within the ten-year scope of this
*Roadmap*, the process---and the intellectual content---must be dynamic.
Beyond the ten-year scope, we must position ourselves to deal with
future national security needs. Ten years ago it was clear that the
Complex needed 3-D, physics-rich simulation codes that could be
supported by terascale platforms in order to certify stockpile weapons
in the absence of UGTs. Today, it is clear that challenges associated
with Responsive Infrastructure and RRW, the aging stockpile, and
emerging nuclear-nation states call for a predictive simulation
capability supported by petascale capability. As the future unfolds, it
is likely that yet another set of requirements will arise as we strive
to maintain a credible nuclear deterrent and use all of NNSA's nuclear
competencies to guard against technological surprise and other threats
to the nation.

![](media/image14.jpeg){width="8.510416666666666in"
height="5.552083333333333in"}

gloSSArY

Many of the terms used in this document have a specific meaning within
the context of the Stockpile Stewardship Program and the ASC Program.

  ------------------ --------------------------------------------------------
  **Baseline:**      The model of a weapons system calibrated against
                     available data sets. A baseline matches a subset of the
                     data as well as possible through a process of adjusting
                     the free parameters of the models in the codes used to
                     perform the baseline.

  **Capability       A classification of the large parallel computing systems
  machines:**        wherein the system is dedicated to, or capable of being
                     dedicated to, a single calculation. Capability machines
                     are characterized by a job mix with few simultaneous
                     jobs, with individual jobs utilizing 40% or more of the
                     system's compute nodes.

  **Capacity         A classification of parallel computing systems that are
  machines:**        not used as capability machines. A job mix of many
                     simultaneous jobs characterizes capacity machines.
                     Historically, today's capability platforms become
                     tomorrow's capacity machines as technology progresses.

  **Legacy code:**   Application codes that existed prior to the start of the
                     ASC Program, before 1995. In many cases, Legacy codes
                     are no longer being actively developed.

  **Modern code:**   Application codes first developed under the ASC Program,
                     starting after 1995. Some codes that would have been
                     classified as Legacy codes have been significantly
                     redesigned under the ASC Program and are therefore
                     classified as modern codes.

  **Validation:**    A process applied to the model of a phenomenon, where it
                     is determined to what degree the model accurately
                     represents that phenomenon.

  **Veriﬁcation:**   A process applied to an application code, where it is
                     determined that the computer calculation for a
                     particular problem accurately represents the solution of
                     the mathematical model.
  ------------------ --------------------------------------------------------

![](media/image15.jpeg){width="8.459722222222222in"
height="10.417361111111111in"}

![](media/image16.jpeg){width="8.53125in" height="11.03125in"}

[^1]: NNSA L. 102-377 mandated the following: (1) banned testing before
    July 1, 1993, (2) set conditions on a resumption of testing, and (3)
    banned testing after September 1996 unless another nation tested. On
    July 3, 1993, President Clinton extended the moratorium at least
    through September 1994 and subsequently extended the moratorium
    twice more past the September 1996 benchmark.

[^2]: Nuclear Posture Review:
    http://www.defenselink.mil/news/Jan2002/d20020109npr.pdf

[^3]: Ad hoc: tailored or calibrated to experimental results---such as
    'ad hoc models' or 'ad hoc parameters'

[^4]: Alliance Centers: http://www.sandia.gov/NNSA/ASC/univ/univ.html

[^5]: Direct Numerical Simulation (DNS): simulation in computational
    fluid dynamics in which the (Navier-Stokes) equations are
    numerically solved without any turbulence model. Thus, the whole
    range of spatial and temporal scales of the turbulence must be
    resolved. DNS tends to be computationally expensive because of the
    high resolution required.

[^6]: The use of smaller and less-expensive high-performance systems to
    run parallel problems with more modest computational requirements,
    in contrast to capability computing. The main figure of merit,
    metric, in capacity computing is the cost/performance ratio.

[^7]: Anything greater than about 200 teraFLOPs

[^8]: The use of the most powerful supercomputers to solve the largest
    and most demanding problem, in contrast to capacity computing. The
    main figure of merit, metric, in capability computing is time to
    solution.