[Federal Register: December 6, 2004 (Volume 69, Number 233)]
[Notices]
[Page 70475-70480]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr06de04-64]
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NUCLEAR REGULATORY COMMISSION
Notice of Availability of Interim Staff Guidance Documents for
Fuel Cycle Facilities
AGENCY: Nuclear Regulatory Commission.
ACTION: Notice of availability.
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FOR FURTHER INFORMATION CONTACT: Wilkins Smith, Project manager,
Technical Support Group, Division of Fuel Cycle Safety and Safeguards,
Office of Nuclear Material Safety and Safeguards, U.S. Nuclear
Regulatory Commission, Washington, DC 20005-0001. Telephone: (301) 415-
5788; fax number: (301) 415-5370; e-mail: wrs@nrc.gov.
SUPPLEMENTARY INFORMATION:
I. Introduction
The Nuclear Regulatory Commission (NRC) plans to issue Interim
Staff Guidance (ISG) documents for fuel cycle facilities. These ISG
documents provide clarifying guidance to the NRC staff when reviewing
either a license application or a license amendment request for a fuel
cycle facility under 10 CFR part 70. The NRC is soliciting public
comments on the ISG documents which will be considered in the final
versions or subsequent revisions.
II. Summary
The purpose of this notice is to provide the public an opportunity
to review and comment on a draft Interim Staff Guidance document for
fuel cycle facilities. Interim Staff Guidance-10 provides guidance to
NRC staff relative to determining whether the minimum margin of
subcriticality (MoS) is sufficient to provide an adequate assurance of
subcriticality for safety to demonstrate compliance with the
performance requirements of 10 CFR 70.61(d).
III. Further Information
The document related to this action is available electronically at
the NRC's Electronic Reading Room at http://www.nrc.gov/reading-rm/adams.html.
From this site, you can access the NRC's Agencywide
Document Access and Management System (ADAMS), which provides text and
image files of NRC's public documents. The ADAMS ascension number for
the document related to this notice is ML043290270. If you do not have
access to ADAMS or if there are problems in accessing the document
located in ADAMS, contact the NRC Public Document Room (PDR) Reference
staff at 1-800-397-4209, 301-415-4737, or by e-mail to pdr@nrc.gov.
This document may also be viewed electronically on the public
computers located at the NRC's PDR, O 1 F21, One White Flint North,
11555 Rockville Pike, Rockville, MD 20852. The PDR reproduction
contractor will copy documents for a fee. Comments and questions should
be directed to the NRC contact listed above by January 5, 2005.
Comments received after this date will be considered if it is practical
to do so, but assurance of consideration cannot be given to comments
received after this date.
Dated at Rockville, Maryland, this 24th day of November 2004.
For the Nuclear Regulatory Commission.
Melanie A. Galloway,
Chief, Technical Support Group, Division of Fuel Cycle Safety and
Safeguards, Office of Nuclear Material Safety and Safeguards.
Draft--Division of Fuel Cycle Safety and Safeguards Interim Staff
Guidance--10; Justification for Minimum Margin of Subcriticality for
Safety Issue
Technical justification for the selection of the minimum margin of
subcriticality (MoS) for safety, as required by 10 CFR 70.61(d)
Introduction
10 CFR 70.61(d) requires, in part, that licensees demonstrate that
``under normal and credible abnormal conditions, all nuclear processes
are subcritical, including use of an approved margin of subcriticality
for safety.'' To demonstrate subcriticality, licensees perform
validation studies in which critical experiments similar to actual or
anticipated calculations are chosen and are then used to establish a
mathematical criterion for subcriticality for all future calculations.
This criterion is expressed in terms of a limit on the maximum value of
the calculated keff, which will be referred to in this ISG
as the upper subcritical limit (USL). The USL includes allowances for
bias and bias uncertainty as well as an additional margin which will be
referred to hereafter as the minimum margin of subcriticality (MoS).
This MoS has been variously referred to within the nuclear industry as
subcritical margin, arbitrary margin, and administrative margin. The
term MoS will be used throughout this ISG for consistency, but these
terms are frequently used interchangeably. This MoS is an allowance for
any unknown errors in the calculational method that may bias the result
of calculations, beyond those accounted for explicitly in the
calculation of the bias and bias uncertainty.
There is little guidance in the fuel facility Standard Review Plans
(SRPs) as to what constitutes an acceptable MoS. NUREG-1520, Section
5.4.3.4.4, states that the MoS should be pre-approved by the NRC and
that the MoS must ``include adequate allowance for uncertainty in the
methodology, data, and bias to assure subcriticality.'' However, there
is little guidance on how to determine the amount of MoS that is
appropriate. Partly due to the historical lack of guidance, there have
been significantly different margins of subcriticality approved for
different fuel cycle facilities over time. In addition, the different
ways of defining the MoS and calculating keff limits
significantly compound the potential for confusion. The MoS can have a
significant effect on facility operations (e.g., storage capacity and
throughput) and there has therefore been considerable recent interest
in decreasing the margins of subcriticality below what has been
accepted historically. These two factors--the lack of guidance and the
increasing interest in reducing margins of subcriticality--make
clarification of what constitutes acceptable justification for the MoS
necessary. In general, consistent with a risk-informed approach to
regulation, smaller margins of subcriticality require more substantial
technical justification.
The purpose of this ISG therefore is to provide guidance on
determining whether the MoS is sufficient to provide
[[Page 70476]]
an adequate assurance of subcriticality for safety, in accordance with
10 CFR 70.61(d).
Discussion
The neutron multiplication factor of a fissile system
(keff) depends, in general, on many different physical
variables. The factors that can affect the calculated value of
keff may be broadly divided into the following categories:
(1) Geometric form; (2) material composition; and (3) neutron
distribution. The geometric form and material composition of the system
determine--together with the underlying nuclear data (e.g., v, X(E),
and the set of cross section data)--the spatial and energy distribution
of neutrons in the system (i.e., flux and energy spectrum). An error in
the nuclear data or in the modeling of these systems can produce an
error in the calculated value of keff. This difference
between the calculated and true value of keff is referred to
as the bias\1\. The bias is defined as the difference between the
calculated and true values of keff, by the following
equation: [beta] = kcalc - ktrue
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\1\ There are many different ways of computing bias as used in
calculation of the USL. This may be an average bias, a least-squares
fitted bias, a bounding bias, etc., as described in the applicant's
methodology.
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The bias of a critical experiment may be known with a high degree
of confidence because the true (experimental) value is known a priori
(ktrue [ap] 1). Because both the experimental and the
calculational uncertainty are known, there is a determinable
uncertainty associated with the bias. The bias for a calculated system
other than a critical experiment is not typically known with this same
high degree of confidence, because ktrue is not typically
known. The MoS is therefore an allowance for any unknown errors that
may affect the calculated value of keff, beyond those
accounted for explicitly in the bias and bias uncertainty. An MoS is
needed because the critical experiments chosen will, in general,
exhibit somewhat different geometric forms, material compositions, and
neutron spectra from those of actual system configurations, and the
effect of these differences is difficult to quantify. Bias and bias
uncertainty are estimated by calculating the keff of
critical experiments with geometric forms, material compositions, and
neutron spectra similar to those of actual or anticipated calculations.
However, because of the many factors that can effect the bias, it must
be recognized that this is only an estimate of the true bias of the
system; it is not possible to guarantee that all sources of error have
been accounted for during validation. Thus, use of a smaller MoS
requires a greater level of assurance that all sources of uncertainty
and bias have been taken into account and that the bias is known with a
high degree of accuracy. The MoS should be large compared to known
uncertainties in the nuclear data and limitations of the methodology
(e.g., modeling approximations, convergence uncertainties). It should
be noted that this MoS is only needed when subcritical limits are based
on the use of calculational methods, including computer and hand
calculations. The MoS is not needed when subcritical limits are based
on other methods, such as experiment or published data (e.g., widely
accepted handbooks or endorsed industry standards).
Because the nuclear industry has employed widely different
terminology regarding validation and margin, it is necessary to define
the following terms as used in this ISG. These definitions are for
clarity only and are not meant to prescribe any particular terminology.
Bias: The difference between the calculated and true values of
keff for a fissile system or set of systems.
Bias Uncertainty: The calculated uncertainty in the bias as
determined by a statistical method.
Margin of subcriticality (MoS): Margin in keff applied
in addition to bias and bias uncertainty to ensure subcriticality (also
known as subcritical, arbitrary, or administrative margin). This term
is shorthand for ``minimum margin of subcriticality''.
Margin of safety: Margin in one or more system parameters that
represents the difference between the value of the parameter at which
it is controlled and the value at which the system becomes critical.
(This represents an additional margin beyond the MoS.)
Upper Subcritical Limit: The maximum allowable keff
value for a system. Generally, the USL is defined by the equation USL =
1-bias-bias uncertainty-MoS.
Subcritical Limit: The value of a system parameter at which it is
controlled to ensure criticality safety, and at which keff
does not exceed the USL (also known as safety limit).
Operating Limit: The value of a system parameter at which it is
administratively controlled to ensure that the system will not exceed
the subcritical limit.\2\
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\2\ Not all licensees have a separate subcritical and operating
limit. Use of administrative operating limits is optional, because
the subcritical limit should conservatively take parametric
tolerances into account.
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If the USL is defined as described above, then the MoS represents
the difference between the average calculated keff
(including uncertainties) and the USL, thus:
MoS = (1-bias-bias uncertainty)-USL.
There are many factors that can affect the code's ability to
accurately calculate keff and that can thus impact the
analyst's confidence in the estimation of the bias. Some of these
factors are described in detail below.
Benchmark Similarity
Because the bias of calculations is estimated based on critical
benchmarks with similar geometric form, material composition, and
neutronic behavior to the systems being evaluated, the degree of
similarity between benchmarks and actual or anticipated calculations is
a key consideration in determining the appropriate MoS. The more
closely the benchmarks represent the characteristics of systems being
validated, the more confidence exists in the calculated bias and bias
uncertainty.
Allowing a comparison of the chosen benchmarks to actual or
anticipated calculations requires that both the experiments and the
calculations be described in sufficient detail to permit independent
verification of results. This may be accomplished by submitting input
decks for both benchmarks and calculations, or by providing detailed
drawings, tables, or other such data to the NRC to permit a detailed
comparison of system parameters.
In evaluating benchmark similarity, some parameters are obviously
more significant than others. The parameters that can have the greatest
effect on the calculated keff of the system are those that
are most significant. Historically, some parameters have been used as
trending parameters because these are the parameters that are expected
to have the greatest effect on the bias. They include the moderator-to-
fuel ratio (e.g., H/U, H/X, v\m\/v\f\), isotopic abundance (e.g.,
\235\U, \239\Pu, or overall Pu-content), and parameters characterizing
the neutron spectrum (e.g., energy of average lethargy causing fission
(EALF), or average energy group (AEG)). Other parameters, such as
material density or overall geometric shape, are generally considered
to be of less importance. Care should be taken that, when basing
justification for a reduced MoS on the similarity of benchmarks to
actual or anticipated calculations, all important system
characteristics that can affect the bias have been taken into
consideration. There are several ways to demonstrate that the chosen
benchmarks are sufficiently similar to actual or anticipated
calculations:
[[Page 70477]]
1. NUREG/CR-6698, ``Guide to Validation of Nuclear Criticality
Safety Calculational Method,'' Table 2.3, contains a set of screening
criteria for determining benchmark applicability. As is stated in the
NUREG, these criteria were arrived at by consensus among experienced
NCS specialists and may be considered conservative. The NRC staff
considers agreement on all screening criteria to be sufficient
justification for demonstrating benchmark similarity. However, less
conservative (i.e., broader) screening ranges may be used if
appropriately justified.
2. Use of an analytical method that systematically quantifies the
degree of similarity between benchmarks and design applications, such
as Oak Ridge National Laboratory's TSUNAMI code in the SCALE 5 code
package.
TSUNAMI calculates a correlation coefficient indicating the degree
of similarity between each benchmark and calculation in pair-wise
fashion. The appropriate threshold value of the parameter indicating a
sufficient degree of similarity is an unresolved issue with the use of
this method. However, the NRC staff currently considers a correlation
coefficient ck >= 0.95 to be indicative of a strong degree
of similarity. Conversely, a correlation coefficient < 0.90 should not
be used as demonstration of benchmark similarity without significant
additional justification. These observations are tentative and are
based on the staff's observation that benchmarks and calculations
having a correlation of at least 95% also appear to be very similar
based on a traditional comparison of system parameters. TSUNAMI should
not be used as a ``black box,'' but may be used to inform the benchmark
selection process, due to the evolving nature of this tool.
3. Sensitivity studies may be employed to demonstrate that the
system keff is highly insensitive to a particular parameter.
In such cases, a significant error in the parameter will have a small
effect on the system bias. One example is when the number density of
certain trace materials can be shown to have a negligible effect on
keff. Another example is when the presence of a strong
external absorber has only a slight effect on k\eff\. In both cases,
such a sensitivity study may be used to justify why agreement with
regard to a given parameter is not important for demonstrating
benchmark similarity.
4. Physical arguments may be used to demonstrate benchmark
similarity. For example, the fact that oxygen and fluorine are almost
transparent to thermal neutrons (i.e., cross sections are very low) may
be used as justification for why the differences in chemical form
between UO2F2 and UO2 may be ignored.
A combination of the above methods may also prove helpful in
demonstrating benchmark similarity. For example, TSUNAMI may be used to
identify the parameters to which keff is most sensitive, or
a sensitivity study may be used to confirm TSUNAMI results or justify
screening ranges. Care should be taken to ensure that all parameters
which can measurably affect the bias are considered when comparing
chosen benchmarks to calculations. For example, comparison should not
be based solely on agreement in the \235\U fission spectrum if \238\U
or \10\B absorption or \1\H scattering have a significant effect on the
calculated keff. A method such as TSUNAMI that considers the
complete set of reactions and nuclides present should be used rather
than relying on a comparison of only the fission spectra. That all
important parameters have been included can be determined based on a
study of the keff sensitivity, as discussed in the next
section. It is especially important that all materials present in
calculations that can have more than a negligible effect on the bias
are included in the chosen benchmarks. In addition, it is necessary
that if the parameters associated with calculations are outside the
range of the benchmark data, the effect of extrapolating the bias
should be taken into account in setting the USL. This should be done by
making use of trends in the bias. Both the trend and the uncertainty in
the trend should be extrapolated using an established mathematical
method.
Some questions that should be asked in evaluating the chosen
benchmarks include:
Are the critical experiments chosen all high-quality
benchmarks from reliable (e.g., peer-reviewed and widely-accepted)
sources?
Are the benchmarks chosen taken from independent sources?
Do the most important benchmark parameters cover the
entire range needed for actual or anticipated calculations?
Is the number of benchmarks sufficient to establish trends
in the bias across the entire range? (The number depends on the
specific statistical method employed.)
Are all important parameters that could affect the bias
adequately represented in the chosen benchmarks?
System Sensitivity
Sensitivity of the calculated keff to changes in system
parameters is a closely related concept to that of similarity. This is
because those parameters to which keff is most sensitive
should weigh more heavily in evaluating benchmark similarity. If
keff is highly sensitive to a given parameter, an error in
the parameter could be expected to have a significant impact on the
bias. Conversely, if keff is very insensitive to a given
parameter, then an error would be expected to have a negligible impact
on the bias. In the latter case, agreement with regard to that
parameter is not important to establishing benchmark similarity.
Two major ways to determine the system's keff
sensitivity are:
1. The TSUNAMI code in the SCALE 5 code package can be used to
calculate the sensitivity coefficients for each nuclide-reaction pair
present in the problem. TSUNAMI calculates both an integral sensitivity
coefficient (i.e., summed over all energy groups) and a sensitivity
profile as a function of energy group. The sensitivity coefficient is
defined as the fractional change in keff for a 1% change in
the nuclear cross section. It must be recognized that TSUNAMI only
evaluates the keff sensitivity to changes in the nuclear
data, and not to other parameters that could affect the bias and should
be considered.
2. Direct sensitivity calculations can also be used to perturb the
system and gauge the resulting effect on keff. Perturbation
of the atomic number densities can also be used to confirm the integral
sensitivity coefficients calculated by TSUNAMI (as when there is doubt
as to convergence of the adjoint flux).
The relationship between the keff sensitivity and
confidence in the bias is the reason that high-enriched uranium fuel
facilities have historically required a greater MoS than low-enriched
uranium facilities. High-enriched systems tend to be much more
sensitive to changes in the underlying system parameters, and in such
systems, the effect of any errors on the bias would be greatly
magnified. For this same reason, systems involving weapons-grade
plutonium would also be more susceptible to undetected errors than low-
assay mixed oxide (i.e., a few percent Pu). The appropriate amount of
MoS should therefore be commensurate with the sensitivity of the system
to changes in the underlying parameters.
Some questions that should be asked in evaluating the
keff sensitivity include:
How sensitive is keff to changes in the
underlying nuclear data (e.g., cross sections)?
How sensitive is keff to changes in the
geometric form and material composition?
[[Page 70478]]
Is the MoS large compared to the expected magnitude of
changes in keff resulting from errors in the underlying
system parameters?
Neutron Physics of the System
Another consideration that may affect the appropriate MoS is the
extent to which the physical behavior of the system is known. Fissile
systems which are known to be subcritical with a high degree of
confidence do not require as much MoS as systems where subcriticality
is less certain. An example of a system known to be subcritical would
be a finished fuel assembly. These systems typically can only be made
critical when highly thermalized, and due to extensive analysis and
reactor experience, the flooded case is known to be subcritical in
isolation. In addition, the thermal neutron cross sections for
materials in finished reactor fuel have been measured with an
exceptionally high degree of accuracy (as opposed to the unresolved
resonance region). Other examples may include systems consisting of
very simple geometry or other idealized situations, in which there is
strong evidence that the system is subcritical based on comparisons
with highly similar systems in published references such as handbooks
or standards. In these cases, the amount of MoS needed may be
significantly reduced.
An important factor in determining that the neutron physics of the
system is well-known is ensuring that the configuration of the system
is fixed. For example, a finished fuel assembly is subject to tight
quality assurance checks and has a form that is well-characterized and
highly stable. A solution or powder process with a complex geometric
arrangement would be much more susceptible to having its configuration
change to one whose neutron physics is not well-understood. Experience
with similar processes may also be credited.
Some questions that should be asked in evaluating the neutron
physics of the system include:
Is the geometric form and material composition of the
system rigid and unchanging?
Is the geometric form and material composition of the
system subject to strict quality assurance?
Are there other reasons besides criticality calculations
to conclude that the system will be subcritical (e.g., handbooks,
standards, reactor fuel studies)?
How well-known are the cross sections in the energy range
of interest?
Rigor of Validation Methodology
Having a high degree of confidence in the estimated bias and bias
uncertainty requires both that there be a sufficient quantity of well-
behaved benchmarks and that there be a sufficiently rigorous validation
methodology. If either the data or the methodology is not adequate, a
high degree of confidence in the results cannot be attained. The
validation methodology must also be suitable for the data analyzed. For
example, a statistical methodology relying on the data being normally
distributed about the mean keff would not be appropriate to
analyze data that are not normally distributed. A linear regression fit
to data that has a non-linear bias trend would similarly not be
appropriate.
Having a sufficient quantity of well-behaved benchmarks means that:
(1) There are enough (applicable) benchmarks to make a statistically
meaningful calculation of the bias and bias uncertainty; (2) the
benchmarks span the entire range of all important parameters, without
gaps requiring extrapolation or wide interpolation; and (3) the
benchmarks do not display any apparent anomalies. Most of the
statistical methods used rely on the benchmarks being normally
distributed. To test for normality, there must be a statistically
significant number of benchmarks (which may vary depending on the test
employed). If there is insufficient data to verify normality to at
least the 95% confidence level, then a non-parametric technique should
be used to analyze the data. In addition, the benchmarks should provide
a continuum of data across the entire validated range so that any
variation in the bias as a function of important system parameters may
be observed. Anomalies that may cast doubt on the results of the
validation may include the presence of discrete clusters of experiments
having a lower calculated keff than the set of benchmarks as
a whole, an excessive fluctuation in keff values (e.g.,
having a X \2\/N [Gt] 1), or discarding an unusually high number of
benchmarks as outliers (i.e., more than 1-2%).
Having a sufficiently rigorous validation methodology means having
a methodology that is appropriate for the number and distribution of
benchmark experiments, that calculates the bias and bias uncertainty
using an established statistical methodology, that accounts for any
trends in the bias, and that accounts for all apparent sources of
uncertainty in the bias (e.g., the increase in uncertainty due to
extrapolating the bias beyond the range covered by the benchmark data).
In addition, confidence that the code's performance is well-
understood means the bias should be relatively small (i.e., bias [lap]
2%), or else the reason for the bias should be known, and no credit
must be taken for positive bias. If the absolute value of the bias is
very large (especially if the reason for the large bias is unknown),
this may indicate that the calculational method is not very accurate,
and a larger MoS may be appropriate.
Some questions that should be asked in evaluating the data and the
methodology include:
Is the methodology consistent with the distribution of the
data (e.g., normal)?
Are there enough benchmarks to determine the behavior of
the bias across the entire area of applicability?
Does the assumed functional form of the bias represent a
good fit to the benchmark data?
Are there discrete clusters of benchmarks for which the
overall bias appears to be non-conservative (especially consisting of
the most applicable benchmarks)?
Has additional margin been applied to account for
extrapolation or wide interpolation?
Have all apparent bias trends been taken into account?
Has an excessive number of benchmarks been discarded as
statistical outliers?
Performance of an adequate code validation alone is not sufficient
justification for any specific MoS. The reason for this is that
determination of the bias and bias uncertainty is separate from
selection of an appropriate MoS. Therefore, performing an adequate code
validation is not alone sufficient demonstration that an appropriate
MoS has been chosen.
Margin in System Parameters
The MoS is a reflection of the degree of confidence in the results
of the validation analysis; the MoS is a margin in keff to
provide a high degree of assurance that fissile systems calculated to
be subcritical are in fact subcritical. However, there are other types
of margin that can provide additional assurance of subcriticality;
these margins are frequently expressed in terms of the system
parameters rather than keff. It is generally acknowledged
that the margin to criticality in system parameters (termed the margin
of safety) is a better indication of the inherent safety of the system
than margin in keff. In addition to establishing subcritical
limits on controlled system parameters,
[[Page 70479]]
licensees frequently establish operating limits to ensure that
subcritical limits are not exceeded. The difference between the
subcritical limit and the operating limit (if used) of a system
parameter represents one type of margin that may be credited in
justifying a lower MoS than would be otherwise acceptable. This
difference between the subcritical limit and the operating limit should
not be confused with the MoS. Confusion often arises, however, because
systems in which keff is highly sensitive to changes in
process parameters may require both: (1) A large margin between
subcritical and operating limits, and (2) a large MoS. This is because
systems in which keff is highly sensitive to changes in
process parameters are highly sensitive to normal process variations
and to any potential errors. Both the MoS and the margin between the
subcritical and operating limits are thus dependent on the
keff sensitivity of the system.
In addition to the margin between the subcritical and operating
limits, there is also usually a significant amount of conservatism in
the facility's technical practices with regard to modeling. In
criticality calculations, controlled parameters are typically analyzed
at their subcritical limits, whereas uncontrolled parameters are
analyzed at their worst-case credible condition. In addition,
tolerances must be conservatively taken into account. These technical
practices generally result in conservatism of at least several percent
in keff. Examples of this conservatism may include assuming
optimum concentration in solution processes, neglect of neutron
absorbers in structural materials, or requiring at least a 1-inch,
tight-fitting reflector around process equipment. The margin due to
this conservatism may be credited in justifying a smaller MoS than
would otherwise be found acceptable. However, in order to take credit
for this as part of the basis for the MoS, it should be demonstrated
that the technical practices committed to in the license application
will result in a predictable and consistent amount of conservatism in
keff. If this modeling conservatism will not always be
present, it should not be used as justification for the MoS.
Some questions that should be asked in evaluating the margin in
system parameters include:
How much margin in keff is present due to
conservatism in the modeling practices?
Will this margin be present for all normal and credible
abnormal condition calculations?
Normal vs. Abnormal Conditions
Historically, several licensees have distinguished between normal
and abnormal condition keff limits, in that they have a
higher keff limit for abnormal conditions. Separate limits
for normal and abnormal condition keff values are
permissible but are not required.
There is a certain likelihood associated with the MoS that
processes calculated to be subcritical will in fact be critical. A
somewhat higher likelihood is permissible for abnormal than for normal
condition calculations. This is because the abnormal condition should
be at least unlikely to occur, in accordance with the double
contingency principle. That is, achieving the abnormal condition
requires at least one contingency to have occurred and is likely to be
promptly corrected upon detection. In addition, there is often
additional conservatism present in the abnormal condition because
uncontrolled parameters are analyzed at their worst-case credible
conditions.
As stated in NUREG-1718, the fact that abnormal conditions meet the
standard of being at least unlikely from the standpoint of the double
contingency principle may be used to justify having a lower MoS than
would be permissible for normal conditions. In addition, the increased
risk associated with the less conservative MoS should be commensurate
with and offset by the unlikelihood of achieving the abnormal
condition. That is, the likelihood that a process calculated to be
subcritical will be critical increases when going from a normal to a
higher abnormal condition keff limit. If the normal
condition keff limit is acceptable, then the abnormal limit
will also be acceptable provided this increased likelihood is offset by
the unlikelihood of going to the abnormal condition because of the
controls that have been established. If a single keff limit
is used (i.e., no credit for unlikelihood of the abnormal condition),
then it must be determined to be acceptable to cover both normal and
credible abnormal conditions.
Statistical Arguments
Historically, the argument has been used that the MoS can be
estimated based on comparing the results of two statistical methods. In
the USLSTATS code issued with the SCALE code package there are two
methods for calculating the USL: (1) The Confidence Band with
Administrative Margin Approach, which calculates USL-1, and (2) the
Lower Tolerance Band Approach, which calculates USL-2. The MoS is an
input parameter to the Confidence Band Approach but is not included
explicitly in the Lower Tolerance Band Approach. Justification that the
MoS chosen in the Confidence Band Approach is adequate has been based
on a comparison of USL-1 and USL-2 (i.e., the condition that USL-1,
including the chosen MoS, is less than USL-2). However, this
justification is not sufficient.
The condition that USL-1 < USL-2 is necessary, but not sufficient,
to show that an adequate MoS has been selected. These methods are two
different statistical treatments of the data, and a comparison between
them can only demonstrate whether the MoS is sufficient to bound
statistical uncertainties included in the Lower Tolerance Band Approach
but not included in the Confidence Band Approach. There may be other
statistical or non-statistical errors in the calculation of
keff that are not handled in the statistical treatments.
Therefore, the NRC does not consider this an acceptable justification
for selection of the MoS.
Regulatory Basis
In addition to complying with paragraphs (b) and (c) of this
section, the risk of nuclear criticality accidents must be limited by
assuring that under normal and credible abnormal conditions, all
nuclear processes are subcritical, including use of an approved margin
of subcriticality for safety. [10 CFR 70.61(d)]
Technical Review Guidance
Determination of an adequate MoS is strongly dependent upon the
specific processes and conditions at the facility being licensed, which
is largely the reason that different facilities have been licensed with
different limits. Judgement and experience must be employed in
evaluating the adequacy of the proposed MoS. Historically, however, an
MoS of 0.05 in keff has generally been found acceptable for
a typical low-enriched fuel fabrication facility. This will generally
be the case provided there is a sufficient quantity of well-behaved
benchmarks and a sufficiently rigorous validation methodology has been
employed. For systems involving high-enriched uranium or plutonium,
additional MoS may be appropriate to account for the increased
sensitivity of keff to changes in system parameters. There
is no consistent precedent for such facilities, but the amount of
increased MoS should be commensurate with the increased keff
sensitivity of these systems. Therefore, an MoS of 0.05 in
keff for low-enriched fuel facilities or an MoS of 0.1 for
high-
[[Page 70480]]
enriched or plutonium fuel facilities must be justified but will
generally be found acceptable, with the caveats discussed above\3\.
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\3\ NUREG-1718, Section 6.4.3.3.4, states that the applicant
should submit justification for the MoS, but then states that an MoS
of 0.05 is ``generally considered to be acceptable without
additional justification when both the bias and its uncertainty are
determined to be negligible.'' These statements are inconsistent.
The statement about 0.05 being generally acceptable without
additional justification is in error and should be removed from the
next revision to the SRP.
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For facility processes involving unusual materials or new process
conditions, the validation should be reviewed in detail to ensure that
there are no anomalies associated with unique system characteristics.
In any case, the MoS should not be reduced below a minimum of 0.02.
Reducing the MoS below 0.05 for low-enriched processes or 0.1 for
high-enriched or plutonium processes requires substantial additional
justification, which may include:
1. An unusually high degree of similarity between the chosen
benchmarks and anticipated normal and credible abnormal conditions
being validated.
2. Demonstration that the system keff is highly
insensitive to changes in underlying system parameters, such that the
worst credible modeling or cross section errors would have a negligible
effect on the bias.
3. Demonstration that the system being modeled is known to be
subcritical with a high degree of confidence. This requires that there
be other strong evidence in addition to the calculations that the
system is subcritical (such as comparison with highly similar systems
in published references such as handbooks or standards).
4. Demonstration that the validation methodology is exceptionally
rigorous, so that any potential sources of error have been accounted
for in calculating the USL.
5. Demonstration that there is a dependable and consistent amount
of conservatism in keff due to the conservatism in modeling
practices.
In addition, justification of the MoS for abnormal conditions may
include:
6. Demonstration that the increased likelihood of a process
calculated as subcritical being critical is offset by the unlikelihood
of achieving the abnormal condition.
This list is not all-inclusive; other technical justification
demonstrating that there is a high degree of confidence in the
calculation of keff may be used.
Recommendation
The guidance in this ISG should supplement the current guidance in
the NCS chapters of the fuel facility SRPs (NUREG-1520 and -1718). In
addition, NUREG-1718, Section 6.4.3.3.4, should be revised to remove
the following sentence: ``A minimum subcritical margin of 0.05 is
generally considered to be acceptable without additional justification
when both the bias and its uncertainty are determined to be
negligible.''
References
NUREG-1520, ``Standard Review Plan for the Review of a License
Application for a Fuel Cycle Facility''
NUREG-1718, ``Standard Review Plan for the Review of an Application
for a Mixed Oxide (MOX) Fuel Fabrication Facility''
NUREG/CR-6698, ``Guide for Validation of Nuclear Criticality Safety
Calculational Methodology''
NUREG/CR-6361, ``Criticality Benchmark Guide for Light-Water-Reactor
Fuel in Transportation and Storage Packages''
Approved:--------------------------------------------------------------
Date:------------------------------------------------------------------
Director, FCSS
[FR Doc. 04-26688 Filed 12-3-04; 8:45 am]
BILLING CODE 7590-01-P