Modeling the Nuclear Fuel Cycle
AM. Yacout!, J. J. Jacobson”, G. E. Matthern’, S. J. Piet? and A. Moisseytsev!
' Argonne National Laboratory, 9700 S. Cass Avenue
Argonne, IL 60439
? Idaho National Laboratory, 2525 N. Fremont Avenue
Idaho Falls, Idaho 83415
Abstract
The Advanced Fuel Cycle Initiative is developing a system dynamics model as part of their
broad systems analysis of future nuclear energy in the United States. The model will be used to
analyze and compare various proposed development scenarios. The model will also give a better
understanding of the linkages between the various components of the nuclear fuel cycle that
includes uranium resources, reactor number and mix, nuclear fuel type and waste management.
Each of these components is tightly connected to the nuclear fuel cycle but is usually analyzed in
isolation of the other parts. This model will attempt to bridge these components into a single
model for analysis. This work is part of a multi-national laboratory work between Argonne
National Laboratory, Idaho National Laboratory, Sandia National Laboratory and United States
Department of Energy. This paper summarizes the basics of the system dynamics model and
looks at some results from the model.
Keywords: System Dynamics, Nuclear Fuel Cycle, Systems Analysis
1. Introduction
The nuclear fuel cycle represents a complex system with different components and activities that
are combined to provide nuclear energy to a variety of end users. The end uses of nuclear energy
include electricity, process heat, water desalination, district heating, and possibly future
hydrogen production. The fuel cycle system analysis has been for a while part of the
development of the peaceful applications of nuclear energy and part of the global studies of
energy systems [1]. Recently, the standard system dynamics tools, such as VenSIM [2], iThinK
[3], and PowerSim [4], has become a familiar fuel cycle system analysis tools to investigate
issues related to its dynamics on both local and global levels.
Different levels of system dynamics involvement in the nuclear fuel cycle analysis have been
considered. The early activities in this area were related to the Nuclear Strategy Project at
Science Applications International Corp. (SAIC) [5-8] which used simple system dynamics
models to foster an improved technical dialog between policymakers and expert groups in
different areas of interest. Following those simple system dynamic models, complicated models
were developed which considered more details of the fuel cycle and the interplay between the
different components of the cycle [9-12]. Within those models, different levels of system
sophistication were considered. The DYMOND model [10], developed for the Generation IV
(Gen-IV) [11] Fuel Cycle Cross Cut group (FCCG) system studies provided a detailed system
dynamics model for the global nuclear enterprise with different fuel cycle technologies. The
code tracked the mass flow of nuclear materials within the fuel cycle and included different types
of delays and feedbacks associated with the construction of nuclear facilities and the decisions to
build such facilities. Although economics calculations were part of the code development,
however, decisions based on economic estimates were not considered. A step further in
simulating the complexity of the fuel cycle was provided through the DANESS model [12],
which expanded the different fuel cycle technologies and nuclear fuel types, in addition to
allowing for decisions based on economic, experience, environmental, and governmental policy
feedback. The two models have been used extensively in complicated fuel cycle deployment
scenarios for both the international and the US nuclear enterprise [11-18].
The work presented here is focused on the modeling of the future nuclear fuel cycle
developments in the US as part of the Department of Energy (DOE) Advanced Fuel Cycle
Initiative (AFCI) program [19]. The paper describes the DYMOND fuel cycle system dynamics
model and associated delays and possible feedbacks, and the interplay between the different parts
of the system, in addition to preliminary model results.
2. Advanced Fuel Cycle Initiative
The United States Department of Energy (US-DOE) has initiated a program to assess the
capabilities of nuclear power to support the growing need for energy and energy security in the
US. The AFCI‘s fundamental objective is to provide technology options that — if implemented —
would enable long-term growth of nuclear power while improving sustainability and energy
security.
Nuclear energy’s growth, and thereby its contribution to improving sustainability and energy
security, can be enhanced by technology development aimed at the key challenge areas of long
term waste management, nuclear fuel utilization, energy production flexibility and economics.
Thus, AFCI technology development focuses on reducing the long-term environmental burden of
nuclear waste, enhancing the use of nuclear fuel resources, and integrating multiple reactor and
fuel types. Each of these three objectives have elements that support and conflict with the other
objectives. There is no single “optimum” solution; rather there are regions of preferred operation
which depend on time and a range of technical and societal factors (e.g. economics and waste
storage regulations).
A key step in identifying the regions of preferred operation was the development of a version of
the DYMOND [10, 11, 16] system dynamic model, DYMOND-US, to capture the structure of
the system and help determine the key components and identify any fundamental tipping points
(events that cause collapse or un-sustainable growth). DYMOND-US is being used to develop a
better understanding of the linkages between the various components in the system and how the
system will react to change. The results of the model are being used to guide research and
development efforts and to provide decision makers with a transparent tool for considering
multiple strategies for nuclear power development.
Some of the questions the model is helping to answer include the following:
- What alternatives exist to building multiple geologic repositories while still supporting an
expanding role for nuclear energy?
- How can the principles of reduce, reuse, and recycle best be applied to nuclear power
development?
- What types of reactors and fuels will be needed and when will they be needed to minimize
long term waste management, while maintaining economic competitiveness?
- What elements of the nuclear fuel cycle are most sensitive to changes in economics, waste
policy, energy supply options, and development of new technologies? How do we make the
system flexible, robust, and dependable?
The broad systems analysis, which DYMOND-US supports, is a collaborative effort between the
Idaho National Laboratory (INL), Argonne National Laboratory (ANL), and US-DOE Nuclear
Energy Office. This broad system analysis is using a set of analysis models that represents a
complete integrated nuclear energy operating system which covers the life-cycle of the nuclear
fuel cycle activities. Those activities include uranium mining and enrichment, fuel fabrication,
reactor irradiation, spent fuel storage, fuel recycling, partitioned storage, transportation,
packaging, long-term storage, and final waste emplacement at a repository. DYMOND-US
shows composite fuel flows through the system that represent the overall volumes, capacities,
and flows across the nuclear energy complex.
3. DYMOND-US Model
The DYMOND-US model provides simplified representations of actual fuel material flows from
fabrication, reactor irradiation, spent fuel storage, fuel recycling and partitioned storage,
transportation, packaging, and final disposition in long-term storage and at a repository. The
model helps address the questions of recycling options, reactor mix and timing, nuclear fuel
options and waste management options. The overall goal is to help evaluate the mix of reactors,
fuel reprocessing and fabrication, and waste management facility capabilities required and timing
of their implementation for a sustainable nuclear fuel system in the US.
The model includes the following system elements:
Mining & Enrichment
e Current natural uranium stocks (U.S. and international)
e Uranium enrichment facilities (for either enriching natural uranium ore or in some
scenarios enriching recycled uranium)
Fuel Fabrication
e Current US stock of enriched uranium fuel
e Fabrication of fuel that uses transuranics from reprocessed spent fuel
Reactor Park
Current 103 U.S. operating reactors (types, design life)
Reactor Life-time extension status (relicensing)
Reactor specifications for next generations options,(types, e.g., Very High
Temperature Reactors producing hydrogen, and fast reactors)
Deployment schedules for new reactors (of either current type or new types)
Reactor Operations
Burn-up rates for fuel, power output, fuel usage
Reactor refueling intervals and reactor lifetime
Reactor Thermal efficiency
Spent Nuclear Fuel Storage
Mass and composition of Spent Nuclear Fuel inventories
Spent fuel generation rates
Reactor on-site storage capacity (wet and dry)
Recycling and Reuse of Spent Nuclear Fuel
Elemental and isotopic separation parameters and efficiencies
Single and multi recycle strategies
Fresh fuel compositions utilizing recycled radionuclides
Element based stream disposition (recycle, transmutation, low level waste disposal,
long-term storage)
Elemental and isotopic level mass balances and flows
Additional Storage Requirements
Storage capabilities and limitations for short-lived fission products (Cs, Sr)
Storage capabilities and limitations for long-lived fission products(I, Tc)
Storage capabilities and limitations for transuranics (plutonium, americium,
neptunium, and curium) and uranium
Current recycle inventories
e Low-level waste storage
Waste Packaging and Transportation
e Waste package characteristics
e Transportation capabilities (mass/volume capacities, heat loading, packaging)
e Interstate shipment requirements
Repository Disposal
¢ Repository capabilities (mass/volume capacities, heat loading, radiotoxicity,
separated zones)
Not included within the system definition at present
e Facility, site or location specific data
e Waste management treatment processes (High Level Waste treatment)
e Environmental Remediation or Decontamination & Disposal wastes
e International resources or potential interfaces
The DYMOND-US model is organized into a series of interconnected sectors. Each sector
focuses on a particular sector of the overall system. Two of the sectors are discussed here: the
Reactor Park sector which tracks the addition and subtraction of nuclear reactors to the national
operating fleet and the Fuel Cycle sector which tracks the lifecycle of the fuel, from initial
fabrication to placement into long-term storage. There is also a short discussion on the model
interface used in DYMOND-US.
3.1 Reactor Park Sector
The Reactor Park Sector tracks the life cycle of reactors. The structure uses an array
structure to track the different types of reactors, current Light Water Reactors, and several next
generation nuclear power plants (with varying types of coolants — sodium, lead, molten salt, or
helium). Reactors will be ordered at a rate dependent on a demand function, and possibly other
criteria such as materials inventories or other economic factors (economic decision making is not
currently implemented in the model). Once a reactor is ordered it has to be licensed, built,
operated and retired. The basic structure is shown in Figure 1.
a Final
Licencing New Reactors Reactors Begin Reactor Reactors Stiop Reactor
Construction
reactors Rate Fuel Request Rata Aging Rate Order Fuel Rate
Om ltl
Under constr
need fuel
Shutdown rate
Reactors
under lincen’
Reactors
near retiremr
Reactors
tobe built Preoper time Fuel prep time
Figure 1: Reactor Life-Cycle Model
The reactors are tracked through the different stages of development that are represented by
stocks (accumulations) in the form of conveyors that contain the reactors in each stage. The stock
regulators (flows) represent transfer from one stage to another. Every conveyor is governed by a
specific time characteristic (delay). For example, the time delay for “Reactors under
construction” is “Construction time”, which is the time it takes to build a reactor.
The decision to order a new reactor is the driving force for that sector. To determine how many
new reactors to order we need to compare demand with deployed reactors plus reactors being
licensed and reactors under construction. In addition, since licensing and construction of a new
reactor takes time (Licensing time + construction time = pre-operation time) some of the
“Operating Reactors” will retire during this time. Therefore, we need to compare demand
against only operating reactors that are “far from retirement”. “Far from retirement” means
reactors that will not retire during “Pre-operation time”. This is done by dividing operating
reactors into two groups, “Fresh reactors” and “Reactors near retirement”. The conveyor time
for “Fresh Reactors” is “Reactor lifetime” minus “Pre-operation time”; the conveyor time for
“Reactors near retirement” is “Pre-operation time”.
In addition, “under construction need fuel” and “Reactors near shutdown” are two reactor states
that are related to fuel supply. Since fuel fabrication takes time (enrichment time + fabrication
time), fuel supply to a new reactor will be ordered ahead of time so it will be available for reactor
startup. “Reactors near shutdown” does not need new fuel as it is close to shutdown after “Fuel
preparation time”, i.e. “Enrichment time” + “Fuel fabrication time”, and fuel should have been
already available for those reactors.
The previous reactor structure is for new reactors. A second structure was developed to track
legacy reactors, that is, existing reactors that have already been built, and have been operating for
different periods of time. This secondary structure tracks the operation and retirement of all
legacy reactors. Legacy reactors will be retired based on a retirement schedule which can be
approximated as follows. The starting number of reactors is 103 reactors where each reactor
generates 950 MWe. The reactors are scheduled to retire starting the year 2027 and retire at a
linear rate until all are retired by the year 2043. The structure is very similar to the previous
structure without the construction stages (Figure 2).
Legacy Reactors
Legacy Reactor Stop Order
Retirement Rate Fuel Rate
weal roel
Legacy Reactors Legacy Reactors
hear retiremnt near shutdown
Legacy Reactor
Shutdown Rate
Preoper time
Legacy Retirement Fuel prep time
Rate
Figure 2: Existing LWRs Model
3.2 The Fuel Cycle Sector
The fuel cycle model tracks the life-cycle of the nuclear fuel. Considering the once-
through fuel cycle (no fuel reprocessing): there are six stages modeled; mining, enrichment, fuel
fabrication, irradiation in reactor, short-term spent fuel storage, and long-term geological storage
(Figure 3), where there is a delay between each stage (not shown in the figure).
Depleted
Uore 5
Mining Tails
Rate
Enriched Fuel Ready Fuel in ISF interim: lLong Term:
Enrichment
material ‘abrication fuel reactors Storage Storage
Enrichment Enriched U Fabrication Fuel Load SF prod Cool
Rate Rate Rate Rate
Figure 3: Once-Through Fuel Cycle
Mined uranium ore goes to enrichment plants where part of this material is converted into
enriched uranium and the remaining part becomes depleted uranium. Enriched uranium goes to
the fuel fabrication plant, “Fuel fabrication”. A new reactor will not start if there is not enough
fuel to load the reactor. Therefore, we need to know how much fresh fuel is produced and ready
for loading into reactors, “Ready fuel”. Once fuel is loaded into the reactor, it spends a specific
time in-reactor after which it is removed from the reactor as spent fuel. This fuel, because of its
heat load, must be stored locally at the reactor in wet storage for several years, “SF Interim
Storage”. After the spent fuel has cooled sufficiently to allow handling and transportation, the
fuel can be sent to a long-term waste repository, “Long Term Storage”.
The above structure models the “Once-through” fuel cycle. Fuel is used once in a reactor and
then shipped to long-term storage. Another option being considered is to reprocess spent fuel
and recover the usable material (actinides such as Pu, Np, Am, Cm) that is still abundant in the
spent fuel. The recovered material can then be reused as fuel for reactors. This would decrease
the need for mining new uranium ore. Reprocessing could also decrease the required amount of
long-term repository storage.
Figure 4 shows a simple flow of the closed fuel cycle (the current version of the model contains a
much more complex system with different options for the closed fuel cycle) with the added
structure needed to include reprocessing. Reprocessed material can be split into recovered
uranium, plutonium, minor actinides (MA = Np, Am, Cm) and high-level waste (HLW). The
plutonium can be used in new fuel fabrication for mixed oxide fuels (MOX). If other types of
fuel are developed then the other components can also be incorporated.
LJ
HUW in
MA fraction in SF
HLW to Repository
Fraction of Pu in MOX
Deplated}
u
Uore
Fuel to ore
voxrequest |} Tals
MOX fuel
iL. ©
umes U
3! traction a SF umaorat ae teens
vragen Rm
oe
—
Lia Reprbcessed
riprgesune
Pu faction in SF
Repossing|
Tevet —
Falyieation ey SF prod
stored
Rate Rate
Envichme
Mining
Rate
Enriched
materal
Eniiched U
Enrichment time Fuel prep
Rate
Ready
fue!
Fuel
tabsleation]
[spent
Fuel in
reactors
storagg
tel
Fabrication time
Spent fuel
production
Consumed fuel
SF to
Spont fuel Repository
storage time
SF in
Repository
Figure 4: This Figure Shows a Simplified Version of the Complete Fuel Cycle Structure when
Including Recycling.
3.3 Model Interface
The current model was developed using Stella/Ithink Version 8.0 development tool [2].
The model is a set of difference equations that can be solved through numerical integration
according to several techniques available in Stella, such as Euler’s method or a second order or
fourth order Runge-Kutta method. Stella has a very powerful set of tools for developing a user
interface. Figure 5 shows the interface “Home” page. The user can maneuver around the model
from this page by clicking on the button of the section that the user wants to view. Base case
simulations based on current parameters can be performed easily. There are a series of 8
scenarios that have been pre-defined. These are described in more detail in the next section. The
user can select a particular scenario by clicking on the appropriate radio button. Additional
simulations based on management and design criteria can be tested against the base cases. The
interface includes stereo control buttons for starting and stopping a simulation.
Figure 5: Model Main Page
In addition, there are parameter panels for modifying the general parameters, as well as
parameters for each reactor type. Figure 6 shows the parameter panel for general information.
The user can change parameters by editing the values in the tables, by clicking on or off the radio
buttons or by moving the slider button in the slider boxes. If a value has been changed then a U
button appears in the parameter box that the user can click on to reset the value to its original
value. The interface is designed around a point and click environment which minimizes typing
from the user. There are panels for adjusting parameters for each type of reactor, LWR, FBR,
VHTR and LWR MOX.
General Data
JU) | Reactor times, yr we |
USA Demand ¥.
ere ae eel
Rest of the World
Growth Rate
eaeaemecnenenenmesnanes
\U)
Start World Growth
Figure 6: Interface for Changing General Model Parameters.
4.0 Strategies
The model is being designed to answer the questions posed by policy makers related to strategies
for future deployment of nuclear reactors in the US. To do so, it is helpful to consider four
possible strategies. Here, a strategy is a general approach to fuel cycle management that
encompasses a range of options with similar basic characteristics. Typically, a strategy identifies
which materials are recycled (if any), the type of nuclear power plant, the type of spent fuel
processing technology, and which materials go to geologic disposal.
The current U.S. strategy is once through - all the components of spent fuel are kept together
and eventually sent to a geologic repository (Figure 7). The second strategy is limited recycle,
where transuranic elements (e.g., Pu, Np, Am, Cm) are recycled once (Figure 8). Residual
transuranic elements and the long-lived fission products would go to geologic disposal. Uranium
in spent fuel, depleted uranium, and short-lived fission products would be disposed as low-level
waste. This strategy emphasizes use of existing infrastructure and existing technology,
especially current and near-term types of thermal reactors.
Power a DED Electricity
plant ™
Interim
storage
Waste
uranium
Figure 7: Once-Through Strategy
Power
pliant
Waste
uranium
Figure 8: Limited Recycle Strategy
The third strategy is continuous recycle, recycling transuranic elements from spent fuel
repeatedly (Figure 9). Sustained recycle is more technically challenging than limited recycle and
therefore additional R&D and technology deployments would be required. Uranium in spent
fuel can be recycled or disposed. Essentially no transuranic elements would go to geologic
disposal. Long-lived fission products would either go to geologic disposal or some could be
transmuted in power plants. Short-lived fission products would be disposed as low-level waste or
sent to temporary storage. This strategy would primarily use thermal reactors; however, a small
fraction of fast reactors may be required.
Power E
plant
Interim
storage
Waste
q ;
uranium
04-GA50634-08d oe
Figure 9: Continuous Recycle Strategy
The fourth strategy is sustained recycle, which differs from continuous recycle primarily by
enabling the recycle of depleted uranium to significantly extent fuel resources. This strategy
would primarily use fast reactors.
) Electricity
Interim
storage
Waste
uranium
04-GA50534-08e
Figure 10: Sustainable Recycle Strategy
Notice that each of these four strategies can be addressed through the different scenario options that are
provided in the model starting page, Figure 5.
5.0 Sample Scenarios Results
Running the model has produced several interesting results. Looking at available uranium
resources with several best guesses on uranium availability shows uranium resources could run
out before 2100 for the once-through strategy and a 3.2% growth in nuclear power. This is based
on the assumption of high estimate of remaining uranium resources of 12 million tons where
only the US is using the resource. In other words, for an aggressive nuclear power growth,
uranium resources will be expended by the end of the century with the once-through strategy. It
should be noted that additional sources could be discovered if there were an economical driver
for further exploration.
Cumulative U Ore Consumed - 1.8 % Growth
5.00E+03
ZL
4.00E+03 /.
3.00E+03 —oTc
— LWR MOX
2.00E+03
Uranium (kton)
A —=FE
1.00E+03 _
0.00E+00
2000 2020 2040 2060 2080 2100
Year
Figure 11: Comparison of the Amount of Uranium Ore Consumed under Three Different
Strategies, where the Assumed Growth Rate for Energy Demand is 1.8%.
The first comparison examines the amount of uranium ore consumed by different scenarios
(Figure 11). The first scenario is the “Once-through” (OTC) with no reprocessing. The second
scenario is LWR reactors using MOX fuels (LWR MOX; fuel that contains some or all the
transuranics from reprocessed spent fuel). The final scenario utilizes Fast Reactors (FR) with
continuous reprocessing. The comparison shows that the once-through strategy will require
much more uranium resources than either of the two other options. This option might be
acceptable as long as we are not pushing the world limits of available uranium ore; otherwise,
one of the other scenarios becomes more favorable.
The next figure shows the same three scenarios given a higher energy demand growth rate of
3.4%. The once-through scenario requires close to 3 times as much uranium ore as from the
once-through 1.8% growth case. It also requires nearly 3 times as much uranium ore as in the
LWR MOX case.
Cumulative U Ore Consumed - 3.4% Growth
=
8 /
2
> 8000 —oTc
6 WA —LWR MOX
— 6000 —FR
§ 4000
2000 ———
0 ; :
2000 2020 2040 2060 2080 2100
Year
Figure 12: The Amount of Uranium Ore Required to Meet the Demand for Three Different
Strategies for 3.4% Demand Growth Rate
Another example of the model capabilities is shown in Figure 13, which shows the
accumulations of plutonium associated with the different nuclear deployment strategies. The
figure includes the once-through strategy for two types of fuel (high and low burnup fuel), in
addition to the limited and continuous recycling strategies. The comparative plutonium
accumulations provided by the model can guide the policy maker on the future deployment
strategy if that type of accumulations is an important decision making factor.
7000
6000
ZA Limited Recycle
5000 ‘Continous Recycle
———Once-Thru (50 GWa/t)
4000 2 -
g — ‘Once-Thru (100 GWa/t)
i =”
3000
2000
1000
0
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090
Year
Figure 13: Comparison between the Plutonium Accumulations in the Nuclear Fuel Cycle for
Different Deployment Strategies
6.0 Summary
The system dynamics model presented here has the potential of allowing decision makers and
stakeholders to explore long-term behavior and performance of the complex nuclear energy
systems, especially in the context of dynamic processes and changing nuclear deployment
scenarios. The model is currently used in the context of deployment scenarios associated with
the US-DOE Advanced Fuel Cycle Initiative. It has already provided valuable insight into the
future consequences of different deployment strategies and it will continue to do so with the
incorporation of more capabilities into the model.
Acknowledgements
This work was performed under the auspices of the DOE under contract W-31-19-Eng-38.
References:
1.
10.
11.
12.
13.
14.
W. Hafele, “Energy in a Finite World, a Global Systems Analysis,” International Institute for
Applied Systems Analysis (IIASA), Ballinger Publishing Company, Cambridge, MA, 1981.
ITHINK Software, ISEE Systems, Inc.
Vensim, Ventana Systems, Inc., http://www.vensim.com.
PowerSim, Powersim Software, http://www.powersim.com.
V. Reis, “Nuclear Strategy Project,” SAIC, 1998.
R. E. Ellis, “The Use of System Dynamics to Model the System Impacts of the Russian
Brest Reactor Design,” SAIC Report to DOE and ANL, January 2001.
Nuclear Strategies Project Workshop on the Disposition of Excess Weapons Plutonium in
Russia, DTRA and SAIC, Washington D.C., April 2001.
A. M. Yacout, “Disposition of Russian Excess Plutonium,” Nuclear Strategies Project
Workshop, Argonne National Laboratory, December 2001.
Y. Guan, “Systemic Analysis, Mapping, Modeling, and Simulation Applied to the Advanced
Accelerator Applications Program,” ASTM, Inc., Report to DOE and ANL, May 2001.
. A. Moisseytsev. “DYMOND, a Dynamic Model of Nuclear Development,” Argonne
National Laboratory Internal Report, August, 2001.
US-Department of Energy, “A Technology Roadmap for Generation IV Nuclear Energy
Systems,” GIF-002-00, Dec. 2002.
L. Van Den Durpel, A. Yacout, D. Wade, H. Khalil, “DANESS, Dynamic Analysis of
Nuclear System Strategies,” in GLOBAL 2003 Meeting, November 16-20, 2003, New
Orleans, LA, USA.
L. A. Malezynski, et. al., “Regional Dynamic Simulation Modeling and Analysis of
Integrated Energy Futures,” Sandia National Laboratory Report SAND2002-3737, November
2001.
V. H. Reis, M. P. Crozat, A Strategy for Nuclear Power: The Role of Government. San
Diego, Calif. : SAIC, June 2002. Power Choice Model
15.L. Van Den Durpel, D. C. Wade, H. Khalil, A. Yacout, “Dynamic Analysis of Nuclear
Energy System Strategies for Electricity and Hydrogen Production in the USA,” in GLOBAL
2003 Meeting, November 16-20, 2003, New Orleans, LA, USA.
16. A. M. Yacout, R. N. Hill, L. Van Den Durpel, P. J. Finck, E. A. Schneider, C. G. Bathke and
J. S. Herring, “Dynamic Analysis of the AFCI Scenarios,” PHYSOR 2004, Chicago, Illinois,
April 25-29, 2004.
17. A. M. Yacout, L. Van Den Durpel, D. C. Wade, and H. Khalil, “Scenarios for the Expanded
Use of Nuclear Energy,” 2004 International Congress on Advances in Nuclear Power Plant
(ICAPP ’04), Pittsburgh, PA USA, June 13-17, 2004.
18. C. J. Jeong, H. Choi, and A. M. Yacout, “A Sensitivity Analysis for the Environmental Effect
of the DUPIC Fuel Cycle,” ANS Annual Meeting, Pittsburg, PA; June 13-17, 2004.
19. US-DOE, Report to Congress on Advanced Fuel Cycle Initiative: The Future Path for
Advanced Spent Fuel Treatment and Transmutation Research, January 2003.
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