Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60565 

reading-rm/doc-collections/ (ACRS & 

ACNW Mtg schedules/agendas). 

Videoteleconferencing service is 

available for observing open sessions of 

ACRS meetings. Those wishing to use 

this service for observing ACRS 

meetings should contact Mr. Theron 

Brown, ACRS Audio Visual Technician 

(301–415–8066), between 7:30 a.m. and 

3:45 p.m., e.t., at least 10 days before the 

meeting to ensure the availability of this 

service. Individuals or organizations 

requesting this service will be 

responsible for telephone line charges 

and for providing the equipment and 

facilities that they use to establish the 

videoteleconferencing link. The 

availability of videoteleconferencing 

services is not guaranteed. 

Dated: October 12, 2005. 

Andrew L. Bates, 

Advisory Committee Management Officer. 

[FR Doc. E5–5734 Filed 10–17–05; 8:45 am] 

BILLING CODE 7590–01–P 

NUCLEAR REGULATORY 

COMMISSION 

Sunshine Act Meeting Notice 

AGENCY HOLDING THE MEETINGS: Nuclear 

Regulatory Commission. 

DATE: Weeks of October 17, 24, 31, 

November 7, 14, 21, 2005. 

PLACE: Commissioners’ Conference 

Room, 11555 Rockville Pike, Rockville, 

Maryland. 

STATUS: Public and Closed. 

MATTERS TO BE CONSIDERED: 

Week of October 17, 2005 

Tuesday, October 18, 2005 

9:30 a.m. 

Briefing on Decommissioning 

Activities and Status (Public 

Meeting) (Contact: Dan Gillen, (301) 

415–7295.) 

This meeting will be Webcast live at 

the Web address—http://www.nrc.gov. 

Week of October 24, 2005—Tentative 

Wednesday, October 26, 2005 

1:30 p.m. 

Discussion of Security Issues 

(Closed—Ex. 1). 

Thursday, October 27, 2005 

10 a.m. 

Discussion of Security Issues 

(Closed—Ex. 1). 

Week of October 31, 2005—Tentative 

Tuesday, November 1, 2005 

9:30 a.m. 

Briefing on Implementation of DavisBesse Lessons Learned Task Force 

(DBLLTF) Recommendations 

(Public Meeting). (Contact: Brendan 

Moroney, (301) 415–3974.) 

This meeting will be Webcast live at 

the Web address—http://www.nrc.gov. 

Week of November 7, 2005—Tentative 

There are no meetings scheduled for 

the Week of November 7, 2005. 

Week of November 14, 2005—Tentative 

There are no meetings scheduled for 

the Week of November 14, 2005. 

Week of November 21, 2005—Tentative 

Monday, November 21, 2005 

9:30 a.m. 

Briefing on Status of New Reactor 

Issues, Part 1 (Public Meeting). 

(Contact: Laura Dudes, (301) 415–

0146.) 

1:30 p.m. 

Briefing on Status of New Reactor 

Issues, Part 2 (Public Meeting). 

(Contact: Laura Dudes, (301) 415–

0146.) 

These meetings will be Webcast live 

at the Web address—http:// 

www.nrc.gov. 

*The schedule for Commission 

meetings is subject to change on short 

notice. To verify the status of meetings 

call (recording)—(301) 415–1292. 

Contact person for more information: 

Michelle Schroll, (301) 415–1662. 

* * * * * 

The NRC Commission Meeting 

Schedule can be found on the Internet 

at: http://www.nrc.gov/what-we-do/ 

policy-making/schedule.html. 

* * * * * 

The NRC provides reasonable 

accommodation to individuals with 

disabilities where appropriate. If you 

need a reasonable accommodation to 

participate in these public meetings, or 

need this meeting notice or the 

transcript or other information from the 

public meetings in another format (e.g. 

braille, large print), please notify the 

NRC’s Disability Program Coordinator, 

August Spector, at (301) 415–7080, 

TDD: (301) 415–2100, or by e-mail at 

aks@nrc.gov. Determinations on 

requests for reasonable accommodation 

will be made on a case-by-case basis. 

* * * * * 

This notice is distributed by mail to 

several hundred subscribers; if you no 

longer wish to receive it, or would like 

to be added to the distribution, please 

contact the Office of the Secretary, 

Washington, DC 20555 (301) 415–1969). 

In addition, distribution of this meeting 

notice over the Internet system is 

available. If you are interested in 

receiving this Commission meeting 

schedule electronically, please send an 

electronic message to dkw@nrc.gov. 

Dated: October 13, 2005. 

R. Michelle Schroll, 

Office of the Secretary. 

[FR Doc. 05–20881 Filed 10–14–05; 10:32 

am] 

BILLING CODE 7590–01–M 

NUCLEAR REGULATORY 

COMMISSION 

Notice of Availability of Interim Staff 

Guidance Document for Fuel Cycle 

Facilities 

AGENCY: Nuclear Regulatory 

Commission. 

ACTION: Notice of availability. 

FOR FURTHER INFORMATION CONTACT: 

James 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) 415–6459; fax 

number: (301) 415–5370; e-mail: 

jas4@nrc.gov. 

SUPPLEMENTARY INFORMATION: 

I. Introduction 

The Nuclear Regulatory Commission 

(NRC) continues 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 attached draft 

ISG document, which will be 

considered in the final version or 

subsequent revisions. 

II. Summary 

The purpose of this notice is to 

provide the public an opportunity to 

review and comment on a revised draft 

Interim Staff Guidance document for 

fuel cycle facilities. A previous version 

of this draft received substantive 

comments; therefore, to provide the 

public an opportunity to review and 

comment on the revised version, the 

document is being re-issued in draft. 

FCSS-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). 

60566 Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 

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 Documents 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 ML052770515. 

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 November 17, 

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 6th day 

of October 2005. 

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. 

Attachment—Draft FCSS Interim Staff 

Guidance-10, Revision 1, ‘‘Justification 

for Minimum Margin of Subcriticality 

for Safety’’

Prepared by Division of Fuel Cycle 

Safety and Safeguards, Office of 

Nuclear Material Safety and Safeguards 

Issue 

Technical justification for the 

selection of the minimum margin of 

subcriticality for safety for fuel cycle 

facilities, as required by 10 CFR 70.61(d) 

Introduction 

10 CFR 70.61(d) requires, in part, that 

licensees or applicants (henceforth to be 

referred to as ‘‘licensees’’) demonstrate 

that ‘‘under normal and credible 

abnormal conditions, all nuclear 

processes are subcritical, including use 

of an approved margin of subcriticality 

for safety.’’ There are a variety of 

methods that may be used to 

demonstrate subcriticality, including 

use of industry standards, handbooks, 

hand calculations, and computer 

methods. Subcriticality is assured, in 

part, by providing margin between 

actual and expected critical conditions. 

This interim staff guidance (ISG), 

however, only applies to margin used in 

those methods that rely on calculation 

of keff, including deterministic and 

probabilistic computer methods. The 

use of other methods (e.g., use of 

endorsed industry standards, widely 

accepted handbooks, certain hand 

calculations), containing varying 

amounts of margin, is outside the scope 

of this ISG. 

For methods relying on calculation of 

Keff, margin may be provided either in 

terms of limits on physical parameters 

of the system (of which Keff is a 

function), or in terms of limits on Keff

directly, or both. For the purposes of 

this ISG, the term margin of safety will 

be used to refer to the margin to 

criticality in terms of system 

parameters, and the term margin of 

subcriticality (MoS) will refer to the 

margin to criticality in terms of Keff. A 

common approach to ensuring 

subcriticality is to determine a 

maximum Keff limit below which the 

licensee’s calculations must fall. This 

limit will be referred to in this ISG as 

the Upper Subcritical Limit (USL). 

Licensees using calculational methods 

perform validation studies, in which 

critical experiments similar to actual or 

anticipated facility calculations are 

chosen and then analyzed to determine 

the bias and uncertainty in the bias. The 

bias is a measure of the systematic 

differences between calculational 

method results and experimental data. 

The uncertainty in the bias is a measure 

of both the accuracy and precision of 

the calculations and the uncertainty in 

the experimental data. A USL is then 

established that includes allowances for 

bias and bias uncertainty as well as an 

additional margin, to be referred to in 

this ISG as the minimum margin of 

subcriticality (MMS). The MMS is 

variously referred to in the nuclear 

industry as minimum subcritical 

margin, administrative margin, and 

arbitrary margin, and the term MMS 

should be regarded as synonymous with 

those terms. The term MMS will be used 

throughout this ISG, and has been 

chosen for consistency with the rule. 

The MMS is an allowance for any 

unknown errors or uncertainties in the 

method of calculating Keff that may exist 

beyond those which have been 

accounted for explicitly in calculating 

the bias and its uncertainty. 

There is little guidance in the fuel 

facility Standard Review Plans (SRPs) as 

to what constitutes sufficient technical 

justification for the MMS. NUREG–

1520, ‘‘Standard Review Plan for the 

Review of a License Application for a 

Fuel Cycle Facility,’’ Section 5.4.3.4.4, 

states that this margin must include, 

among other uncertainties, ‘‘adequate 

allowance for uncertainty in the 

methodology, data, and bias to assure 

subcriticality.’’ However, there has been 

almost no guidance on how to 

determine an appropriate MMS. Partly 

due to the lack of historical guidance, 

and partly due to differences between 

facilities’ processes and methods of 

calculation, there have been 

significantly different MMS values 

approved for the various fuel cycle 

facilities over time. In addition, the 

different ways licensees have of 

defining margins and calculating Keff

limits have made a consistent approach 

to reviewing Keff limits difficult. Recent 

licensing experience has highlighted the 

need for further guidance to clarify what 

constitutes an acceptable justification 

for the MMS. 

The MMS can have a substantial 

effect on facility operations (e.g., storage 

capacity, throughput) and there has, 

therefore, been considerable recent 

interest in decreasing margin in Keff

below what has been licensed 

previously. In addition, the increasing 

sophistication of computer codes and 

the ready availability of computing 

resources means that there has been a 

gradual move towards more realistic 

(often resulting in less conservative) 

modeling of process systems. These two 

factors—the increasing interest in 

reducing the MMS and the reduction in 

modeling conservatism—make technical 

justification of the MMS more risksignificant than it has been in the past. 

In general, consistent with a riskinformed approach to regulation, a 

smaller MMS requires a more 

substantial technical justification. 

This ISG is only applicable to fuel 

enrichment and fabrication facilities 

licensed under 10 CFR part 70. 

Discussion 

This guidance is applicable to 

evaluating the MMS in methods of 

evaluation that rely on calculation of 

Keff. The Keff value of a fissionable 

system depends, in general, on a large 

number of physical variables. The 

factors that can affect the calculated 

value of Keff may be broadly divided 

into the following categories: (1) The 

geometric configuration; (2) the material 

composition; and (3) the neutron 

distribution. The geometric form and 

material composition of the system 

determine—together with the 

underlying nuclear data (e.g., v,X(E), 

cross-section data)—the spatial and 

energy distribution of neutrons in the 

system (flux and energy spectrum). An 

error in the nuclear data or the 

Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60567 

geometric or material modeling of these 

systems can produce an error in the 

neutron flux and energy spectrum, and 

thus in the calculated value of Keff. The 

bias associated with a single system is 

defined as the difference between the 

calculated and physical values of Keff, 

by the following equation: 

b = kcalc ¥ kphysical

Thus, determining the bias requires 

knowing both the calculated and 

physical Keff values of the system. The 

bias associated with a single critical 

experiment can be known with a high 

degree of confidence, because the 

physical (experimental) value is known 

a priori (kphysical ≈ 1). However, for 

calculations performed to demonstrate 

subcriticality of facility processes (to be 

referred to as ‘‘applications’’), this is not 

generally the case. The bias associated 

with such an application (i.e., not a 

known critical configuration) is not 

typically known with this same high 

degree of confidence, because the actual 

physical Keff of the system is usually not 

known. In practice, the bias is 

determined as the average calculated 

Keff for a set of experiments that cover 

different aspects of the licensee’s 

applications. The bias and its 

uncertainty must be estimated by 

calculating the bias associated with a set 

of critical experiments having geometric 

forms, material compositions, and 

neutron spectra similar to those of the 

application. Because of the large 

number of factors that can affect the 

bias, and the finite number of critical 

experiments available, staff should 

recognize that this is only an estimate of 

the true bias of the system. The 

experiments analyzed cannot cover all 

possible combinations of conditions or 

sources of error that may be present in 

the applications to be evaluated. The 

effect on Keff of geometric, material, or 

spectral differences between critical 

experiments and applications cannot be 

known with precision. Therefore, an 

additional margin (MMS) must be 

applied to allow for the effects of any 

unknown uncertainties that may exist in 

the calculated value of Keff beyond those 

accounted for in the calculation of the 

bias and its uncertainty. As the MMS 

decreases, there needs to be a greater 

level of assurance that the various 

sources of bias and uncertainty have 

been taken into account, and that the 

bias and uncertainty are known with a 

high degree of accuracy. In general, the 

more similar the critical experiments are 

to the applications, the more confidence 

there is in the estimate of the bias and 

the less MMS is needed. 

In determining an appropriate MMS, 

the reviewer should consider the 

specific conditions and process 

characteristics present at the facility in 

question. However, the MMS should not 

be reduced below 0.02. The nuclear 

cross sections are not generally known 

to better than ∼1–2%, and thus it is not 

possible to have a greater level of 

assurance in the calculated results than 

this. Moreover, errors in the criticality 

codes have been discovered over time 

that have produced Keff differences of 

roughly this same magnitude of 1–2% 

(e.g., Information Notice 2005–13, 

‘‘Potential Non-Conservative Error in 

Modeling Geometric Regions in the 

KENO-V.a Criticality Code’’). 

Staff should recognize the important 

distinction between ensuring that 

processes are safe and ensuring that 

they are adequately subcritical. The 

value of Keff is a direct indication of the 

degree of subcriticality of the system, 

but is not fully indicative of the degree 

of safety. A system that is very 

subcritical (i.e., with Keff ß1) may have 

a small margin of safety if a small 

change in a process parameter can result 

in criticality. An example of this would 

be a UO2 powder storage vessel, which 

is subcritical when dry, but may require 

only the addition of water for criticality. 

Similarly, a system with a small MoS 

(i.e., with Keff ß1) may have a very large 

margin of safety if it cannot credibly 

become critical. An example of this 

would be a natural uranium system in 

light water, which may have a Keff value 

close to 1 but will never exceed 1. 

Because of this, a distinction should 

be made between the margin of 

subcriticality and the margin of safety. 

Although a variety of terms are in use 

in the nuclear industry, the term margin 

of subcriticality will be taken to mean 

the difference between the actual 

(physical) value of keff and the value of 

keff at which the system is expected to 

be critical. The term margin of safety 

will be taken to mean the difference 

between the actual value of a parameter 

and the value of the parameter at which 

the system is expected to be critical. The 

appropriate MMS depends only on the 

confidence that applications calculated 

to be subcritical will be subcritical. It 

does not depend on other aspects of the 

process (e.g., safety of the process or the 

ability to control parameters within 

certain bounds) that may need to be 

reviewed as part of an overall licensing 

review. 

There are a variety of different 

approaches that a licensee could choose 

in justifying the MMS. Some of these 

approaches and means of reviewing 

them are described in the following 

sections, in no particular preferential 

order. Many of these approaches consist 

of qualitative arguments, and therefore 

there will be some degree of subjectivity 

in determining the adequacy of the 

MMS. Because the MMS is an allowance 

for unknown (or difficult to identify or 

quantify) errors, the reviewer must 

ultimately exercise his or her best 

judgement in determining whether a 

specific MMS is justified. Thus, the 

topics listed below should be regarded 

as factors the reviewer should take into 

consideration in exercising that 

judgement, rather than any kind of 

prescriptive checklist. 

The reviewer should also bear in 

mind that the licensee is not required to 

use any or all of these approaches, but 

may choose an approach that is 

applicable to its facility or a particular 

process within its facility. While it may 

be desirable and convenient to have a 

single keff limit or MMS value (and 

single corresponding justification) 

across an entire facility, it is not 

necessary for this to be the case. The 

MMS may be easier to justify for one 

process than for another, or for a limited 

application versus generically for the 

entire facility. The reviewer should 

expect to see various combinations of 

these approaches, or entirely different 

approaches, used, depending on the 

nature of the licensee’s processes and 

methods of calculation. Any approach 

used must ultimately lead to a 

determination that there is adequate 

assurance of subcriticality. 

(1) Conservatism in the Calculational 

Models 

The margin in keff produced by the 

licensee’s modeling practices, together 

with the MMS, provide the margin 

between actual conditions and expected 

critical conditions. In terms of the 

subcriticality criterion taken from ANSI/ 

ANS–8.17–1984 (R1997), ‘‘Criticality 

Safety Criteria for the Handling, Storage, 

and Transportation of LWR Fuel 

Outside Reactors’’ (as explained in 

Appendix A): MoS ≥ DKm + DKsa

where Dkm is the MMS and Dksa is the 

margin in keff due to conservative 

modeling of the system (i.e., 

conservative values of system 

parameters). 

Two different applications for which 

the sums on the right hand side of the 

equation above are equal to each other 

are equally subcritical. Assurance of 

subcriticality may thus be provided by 

specifying a margin in keff (Dkm), or 

specifying conservative modeling 

practices (Dksa), or some combination 

thereof. This principle will be 

particularly useful to the reviewer 

evaluating a proposed reduction in the 

currently approved MMS; the review of 

such a reduction should prove 

straightforward in cases in which the 

overall combination of modeling 

60568 Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 

conservatism and MMS has not 

changed. Because of this straightforward 

quantitative relationship, any modeling 

conservatism that has not been 

previously credited should be 

considered before examining other 

factors. Cases in which the overall MoS 

has decreased may still be acceptable, 

but would have to be justified by other 

means. 

In evaluating justification for the 

MMS relying on conservatism in the 

model, the reviewer should consider 

only that conservatism in excess of any 

manufacturing tolerances, uncertainties 

in system parameters, or credible 

process variations. That is, the 

conservatism should consist of 

conservatism beyond the worst-case 

normal or abnormal conditions, as 

appropriate, including allowance for 

any tolerances. Examples of this added 

conservatism may include assuming 

optimum concentration in solution 

processes, neglecting neutron absorbers 

in structural materials, or requiring 

minimum reflector conditions (e.g., at 

least a 1-inch, tight-fitting reflector 

around process equipment). These 

technical practices used to perform 

criticality calculations generally result 

in conservatism of at least several 

percent in keff. To credit this as part of 

the justification for the MMS, the 

reviewer should have assurance that the 

modeling practices described will result 

in a predictable and dependable amount 

of conservatism in keff. In some cases, 

the conservatism may be processdependent, in which case it may be 

relied on as justification for the MMS 

for a particular process. However, only 

modeling practices that result in a 

global conservatism across the entire 

facility should be relied on as 

justification for a site-wide MMS. 

Ensuring predictable and dependable 

conservatism includes verifying that 

this conservatism will be maintained 

over the facility lifetime, such as 

through the use of license commitments 

or conditions. 

If the licensee has a program that 

establishes operating limits (to ensure 

that subcritical limits are not exceeded) 

below subcritical limits determined in 

nuclear criticality safety evaluations, the 

margin provided by this (optional) 

practice may be credited as part of the 

conservatism. In such cases, the 

reviewer should credit only the 

difference between operating and 

subcritical limits that exceeds any 

tolerances or process variation, and 

should ensure that operating limits will 

be maintained over the facility lifetime, 

through the use of license commitments 

or conditions. 

Some questions that the reviewer may 

ask in evaluating the use of modeling 

conservatism as justification for the 

MMS include: 

• How much margin in keff is 

provided due to conservatism in 

modeling practices? 

• How much of this margin exceeds 

allowance for tolerances and process 

variations? 

• Is this margin specific to a 

particular process or does it apply to all 

facility processes? 

• What provides assurance that this 

margin will be maintained over the 

facility lifetime? 

(2) Validation Methodology and Results 

Assurance of subcriticality for 

methods that rely on the calculation of 

keff requires that those methods be 

appropriately validated. One of the 

goals of validation is to determine the 

method’s bias and the uncertainty in the 

bias. After this has been done, an 

additional margin (MMS) is specified to 

account for any additional uncertainties 

that may exist. The appropriate MMS 

depends, in part, on the degree of 

confidence in the validation results. 

Having a high degree of confidence in 

the bias and bias uncertainty requires 

both that there be sufficient (for the 

statistical method used) applicable 

benchmark-quality experiments and that 

there be a rigorous validation 

methodology. If either the data or the 

methodology is deficient, a high degree 

of confidence in the results cannot be 

attained, and a larger MMS may need to 

be employed than would otherwise be 

acceptable. Therefore, although 

validation and determining the MMS 

are separate exercises, they are related. 

The more confidence one has in the 

validation results, the less additional 

margin (MMS) is needed. The less 

confidence one has in the validation 

results, the more MMS is needed. 

Any review of a licensing action 

involving the MMS should involve 

examination of the licensee’s validation 

methodology and results. While there is 

no clear quantifiable relationship 

between the validation and MMS (as 

exists with modeling conservatism), 

several aspects of validation should be 

considered before making a qualitative 

determination of the adequacy of the 

MMS. 

There are four factors that the 

reviewer should consider in evaluating 

the validation: (1) The similarity of 

benchmark experiments to actual 

applications; (2) sufficiency of the data 

(including the number and quality of 

experiments); (3) adequacy of the 

validation methodology; and (4) 

conservatism in the calculation of the 

bias and its uncertainty. These factors 

are discussed in more detail below. 

Similarity of Benchmark Experiments 

Because the bias and its uncertainty 

must be estimated based on critical 

experiments having similar geometric 

form, material composition, and 

neutronic behavior to specific 

applications, the degree of similarity 

between the critical experiments and 

applications is a key consideration in 

determining the appropriateness of the 

MMS. The more closely critical 

experiments represent the 

characteristics of applications being 

validated, the more confidence the 

reviewer has in the estimate of the bias 

and the bias uncertainty for those 

applications. 

The reviewer must understand both 

the critical experiments and 

applications in sufficient detail to 

ascertain the degree of similarity 

between them. Validation reports 

generally contain a description of 

critical experiments (including source 

references). The reviewer may need to 

consult these references to understand 

the physical characteristics of the 

experiments. In addition, the reviewer 

may need to consult process 

descriptions, nuclear criticality safety 

evaluations, drawings, tables, input 

files, or other information to understand 

the physical characteristics of 

applications. The reviewer must 

consider the full spectrum of normal 

and abnormal conditions that may have 

to be modeled when evaluating the 

similarity of the benchmarks to 

applications. 

In evaluating the similarity of 

experiments to applications, the 

reviewer must recognize that some 

parameters are more significant than 

others to accurately calculate keff. The 

parameters that have the greatest effect 

on the calculated keff of the system are 

those that are most important to match 

when choosing critical experiments. 

Because of this, there is a close 

relationship between similarity of 

benchmarks to applications and system 

sensitivity. Historically, certain 

parameters have been used to trend the 

bias because these are the parameters 

that have been found to have the 

greatest effect on the bias. These 

parameters include the moderator-tofuel ratio (e.g., H/U, H/X, vm/vf

), 

isotopic abundance (e.g., uranium-235 

(235U), plutonium-239 (239Pu), or overall 

Pu-to-uranium ratio), and parameters 

that characterize the neutron energy 

spectrum (e.g., energy of average 

lethargy causing fission (EALF), average 

energy group (AEG)). Other parameters, 

such as material density or overall 

Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60569 

geometric shape, are generally 

considered to be of less importance. The 

reviewer should consider all important 

system characteristics that can 

reasonably be supposed to affect the 

bias. For example, the critical 

experiments should include any 

materials that can have an appreciable 

effect on the calculated keff, so that the 

effect due to the cross sections of those 

materials is included in the bias. 

Furthermore, these materials should 

have at least the same reactivity worth 

in the experiments (which may be 

evidenced by having similar number 

densities) as in the applications. 

Otherwise, the effect of any bias from 

the underlying cross sections or the 

assumed material composition may be 

masked in the applications. It is also 

important that the materials be present 

in a statistically significant number of 

experiments having similar neutron 

spectra to the application. Conversely, 

materials that do not have an 

appreciable effect on the bias may be 

neglected and would not have to be 

represented in the critical experiments. 

Merely having critical experiments 

that are representative of applications is 

the minimum acceptance criterion, and 

does not alone justify having any 

particular value of the MMS. There are 

some situations, however, in which 

there is an unusually high degree of 

similarity between the critical 

experiments and applications, and in 

these cases, this fact may be credited as 

justification for having a smaller MMS 

than would otherwise be acceptable. If 

the critical experiments have geometric 

forms, material compositions, and 

neutron spectra that are nearly 

indistinguishable from those of the 

applications, this may be justification 

for reducing the MMS. For example, 

justification for having a small MMS for 

finished fuel assemblies could include 

selecting critical experiments consisting 

of fuel assemblies in water, where the 

fuel has nearly the same pellet diameter, 

pellet density, cladding materials, pitch, 

absorber content, enrichment, and 

neutron energy spectrum as the 

licensee’s fuel. In this case, the 

validation should be very specific to 

this type of system, because including 

other types of benchmark experiments 

could mask variations in the bias. 

Therefore, this type of justification is 

generally easiest when the area of 

applicability (AOA) is very narrowly 

defined. The reviewer should pay 

particular attention to abnormal 

conditions. In this example, damage to 

the fuel or partial flooding may 

significantly affect the applicability of 

the critical experiments. 

There are several tools available to the 

reviewer to ascertain the degree of 

similarity between critical experiments 

and applications. Some of these are 

listed below: 

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 nuclear criticality safety 

specialists and may be considered to be 

conservative. The reviewer should consider 

agreement on all screening criteria to be 

justification for demonstrating a very high 

degree of benchmark similarity. (Agreement 

on the most significant screening criteria for 

a particular system should be considered as 

demonstration of an acceptable degree of 

benchmark similarity.) Less conservative 

(i.e., broader) screening criteria may also be 

acceptable, if appropriately justified. 

2. Analytical methods that systematically 

quantify the degree of similarity between a 

set of critical experiments and applications 

in pair-wise fashion may be used. One 

example of this is the TSUNAMI code in the 

SCALE 5 code package. One strength of 

TSUNAMI is that it calculates an overall 

correlation that is a quantitative measure of 

the degree of similarity between an 

experiment and an application. Another 

strength is that this code considers all the 

nuclear phenomena and underlying cross 

sections and weighs them by their 

importance to the calculated keff (i.e., 

sensitivity of keff to the data). The NRC staff 

currently considers a correlation coefficient 

of ck ≥0.95 to be indicative of a very high 

degree of similarity. This is based on the 

staff’s experience comparing the results from 

TSUNAMI to those from a more traditional 

screening criterion approach. Conversely, a 

correlation coefficient less than 0.90 should 

not be used as a demonstration of a high 

degree of benchmark similarity. Because of 

limited use of the code to date, these 

observations should be considered tentative 

and thus the reviewer should not use 

TSUNAMI as a ‘‘black box,’’ or base 

conclusions of adequacy solely on its use. 

However, it may be used to test a licensee’s 

statement that there is a high degree of 

similarity between experiments and 

applications. 

3. Traditional parametric sensitivity 

studies may be employed to demonstrate that 

keff is highly sensitive or insensitive to a 

particular parameter. For example, if a 50% 

reduction in the 10B cross section is needed 

to produce a 1% change in the system keff, 

then it can be concluded that the system is 

highly insensitive to the boron content, in the 

amount present. This is because a credible 

error in the 10B cross section of a few percent 

will have a statistically insignificant effect on 

the bias. Therefore, in the amount present, 

the boron content is not a parameter that is 

important to match in order to conclude that 

there is a high degree of similarity between 

benchmarks and applications. 

4. Physical arguments may demonstrate 

that keff is highly sensitive or insensitive to 

a particular parameter. For example, the fact 

that oxygen and fluorine are almost 

transparent to thermal neutrons (i.e., cross 

sections are very low) may justify why 

experiments consisting of UO2F2 may be 

considered similar to UO2 or UF4

applications, provided that both experiments 

and applications occur in the thermal energy 

range. 

The reviewer should ensure that all 

parameters which can measurably affect 

the bias are considered when assessing 

benchmark similarity. For example, 

comparison should not be based solely 

on agreement in the 235U fission 

spectrum for systems in which the 

system keff is highly sensitive to 238U 

fission, 10B absorption, or 1H scattering. 

A method such as TSUNAMI that 

considers the complete set of reactions 

and nuclides present can be used to 

rank the various system sensitivities, 

and to thus determine whether it is 

reasonable to rely on the fission 

spectrum alone in assessing the 

similarity of benchmarks to 

applications. 

Some questions that the reviewer may 

ask in evaluating reliance on benchmark 

similarity as justification for the MMS 

include: 

• Do the benchmarks cover all 

geometric forms, material compositions, 

and neutron energy spectra expected in 

applications? 

• Are the materials present with at 

least the same reactivity worth as in 

applications? 

• Do the licensee’s criteria for 

determining whether experiments are 

sufficiently similar to applications 

consider all nuclear reactions and 

nuclides that could affect the bias? 

Sufficiency of the Data 

Another aspect of evaluating the 

selected benchmarks for a specific MMS 

is ensuring that there is a sufficient 

number of benchmark quality 

experiments to determine the bias 

across the entire AOA. Having a 

sufficient number of benchmark-quality 

experiments means that: (1) There are 

enough (applicable) experiments to 

make a statistically meaningful 

calculation of the bias and its 

uncertainty; (2) the experiments 

somewhat evenly span the entire range 

of all the important parameters, without 

gaps requiring extrapolation or wide 

interpolation; and (3) the experiments 

are all benchmark-quality experiments. 

The number of benchmarks needed is 

dependent on the statistical method 

used to analyze the data. For example, 

some methods require a minimum 

number of data points to reliably 

determine whether the data are 

normally distributed. Merely having a 

large number of experiments is not 

60570 Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 

sufficient to provide confidence in the 

validation result, if the experiments are 

not applicable to the application. The 

reviewer should particularly examine 

whether consideration of only the most 

applicable experiments would result in 

a larger negative bias (and thus a lower 

USL) than that determined based on the 

full set of experiments. The experiments 

should also be sufficiently wellcharacterized (including experimental 

parameters and their uncertainties) to be 

considered benchmark experiments. 

They should be drawn from established 

sources (such as from the International 

Handbook of Evaluated Criticality 

Safety Benchmark Experiments 

(IHECSBE), laboratory reports, or peerreviewed journals). 

Some questions that the reviewer may 

ask in evaluating the number and 

quality of benchmark experiments as 

justification for the MMS include: 

• Are the critical experiments chosen 

all high-quality benchmarks from 

reliable (e.g., peer-reviewed and widelyaccepted) sources? 

• Are the critical experiments chosen 

taken from multiple independent 

sources, to minimize the possibility of 

systematic errors? 

• Have the experimental uncertainties 

associated with the critical experiments 

been provided and used in calculating 

the bias and bias uncertainty? 

• Is the number and distribution of 

critical experiments sufficient to 

establish trends in the bias across the 

entire range of parameters? 

• Is the number of critical 

experiments commensurate with the 

statistical methodology being used? 

Validation Methodological Rigor 

Having a sufficiently rigorous 

validation methodology means having a 

methodology that is appropriate for the 

number and distribution of critical 

experiments, that calculates the bias and 

its 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.) Examples of 

deficiencies in the validation 

methodology may include: (1) Using a 

statistical methodology relying on the 

data being normally distributed about 

the mean keff to analyze data that are not 

normally distributed; (2) using a linear 

regression fit on data that has a nonlinear dependence on a trending 

parameter; (3) use of a single pooled 

bias when very different types of critical 

experiments are being evaluated in the 

same validation. These deficiencies 

serve to decrease confidence in the 

validation results and may warrant 

additional margin (i.e., a larger MMS). 

Additional guidance on some of the 

more commonly observed deficiencies 

is provided below. 

The assumption that data is normally 

distributed is generally valid, unless 

there is a strong trend in the data or 

different types of critical experiments 

with different mean calculated keff

values are being combined. Tests for 

normality require a minimum number of 

critical experiments to attain a specified 

confidence level (generally 95%). If 

there is insufficient data to verify that 

the data are normally distributed, or the 

data are shown to be not normally 

distributed, a non-parametric technique 

should be used to analyze the data. 

The critical experiments chosen 

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. The presence of discrete 

clusters of experiments having a lower 

calculated keff than the set of critical 

experiments as a whole should be 

examined closely, to determine if there 

is some systematic effect common to a 

particular type of calculation that makes 

use of the overall bias non-conservative. 

Because the bias can vary with system 

parameters, if the licensee has combined 

different subsets of data (e.g., solutions 

and powders, low- and high-enriched, 

homogeneous and heterogeneous), the 

bias for the different subsets should be 

analyzed. In addition, the goodness-offit for any function used to trend the 

bias should be examined to ensure it is 

appropriate to the data being analyzed. 

If critical experiments do not cover 

the entire range of parameters needed to 

cover anticipated applications, it may be 

necessary to extend the AOA by making 

use of trends in the bias. Any 

extrapolation (or wide interpolation) of 

the data should be done by means of an 

established mathematical methodology 

that takes into account the functional 

form of both the bias and its 

uncertainty. The extrapolation should 

not be based on judgement alone, such 

as by observing that the bias is 

increasing in the extrapolated range, 

because this may not account for the 

increase in the bias uncertainty that will 

occur with increasing extrapolation. The 

reviewer should independently confirm 

that the derived bias is still valid in the 

extrapolated range and should ensure 

that the extrapolation is not large. 

NUREG/CR–6698 states that critical 

experiments should be added if the data 

must be extrapolated more than 10%. If 

the extrapolation is too large, new 

factors that could affect the bias may be 

introduced as the physical phenomena 

in the system change. The reviewer 

should not view validation as a purely 

mathematical exercise, but should bear 

in mind the neutron physics and 

underlying physical phenomena when 

interpreting the results. 

Discarding an unusually large number 

of critical experiments as outliers (i.e., 

more than 1–2%) should also be viewed 

with some concern. Apparent outliers 

should not be discarded based purely 

upon judgement or statistical grounds 

(such as causing the data to fail tests for 

normality), because they could be 

providing valuable information on the 

method’s validity for a particular 

application. The reviewer should verify 

that there are specific defensible 

reasons, such as reported 

inconsistencies in the experimental 

data, for discarding any outliers. If any 

of the critical experiments from a 

particular data set are discarded, the 

reviewer should examine other 

experiments included to determine 

whether they may be subject to the same 

systematic errors. Outliers should be 

examined carefully especially when 

they have a lower calculated keff than 

the other experiments included. 

NUREG–1520 states that the MoS 

should be large compared to the 

uncertainty in the bias. The observed 

spread of the data about the mean keff

should be examined as an indicator of 

the overall precision of the calculational 

method. The reviewer should ascertain 

whether the statistical method of 

validation considers both the observed 

spread in the data and the experimental 

and calculational uncertainty in 

determining the USL. The reviewer 

should also evaluate whether the 

observed spread in the data is consistent 

with the reported uncertainty (e.g., 

whether X2/N ≈ 1). If the spread in the 

data is larger than or comparable to the 

MMS, then the reviewer should 

consider whether additional margin 

(i.e., a larger MMS) is needed. 

As a final test of the code’s accuracy, 

the bias should be relatively small (i.e., 

bias ≈ 2 percent), or else the reason for 

the bias should be determined. No 

credit should be taken for positive bias, 

because this would result in making 

changes in a non-conservative direction 

without having a clear understanding of 

those changes. If the absolute value of 

the bias is very large—and especially if 

the reason for the large bias cannot be 

determined—this may indicate that the 

calculational method is not very 

accurate, and a larger MMS may be 

appropriate. 

Some questions that the reviewer may 

ask in evaluating the rigor of the 

Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60571 

validation methodology as justification 

for the MMS include: 

• Are the results from use of the 

methodology consistent with the data 

(e.g., normally distributed)? 

• Is the normality of the data 

confirmed prior to performing statistical 

calculations? If the data does not pass 

the tests for normality, is a nonparametric method used? 

• Does the assumed functional form 

of the bias represent a good fit to the 

critical experiments? Is a goodness-of-fit 

test performed? 

• Does the method determine a 

pooled bias across disparate types of 

critical experiments, or does it consider 

variations in the bias for different types 

of experiments? Are there discrete 

clusters of experiments for which the 

bias appears to be non-conservative? 

• Has additional margin been applied 

to account for extrapolation or wide 

interpolation? Is this done based on an 

established mathematical methodology? 

• Have critical experiments been 

discarded as apparent outliers? Is there 

a valid reason for doing so? 

Performing an adequate code 

validation is not by itself sufficient 

justification for any specific MMS. The 

reason for this is that the validation 

analysis determines the bias and its 

uncertainty, but not the MMS. The 

MMS is added after the validation has 

been performed to provide added 

assurance of subcriticality. However, 

having a validation methodology that 

either exceeds or falls short of accepted 

standards for validation may be a basis 

for either reducing or increasing the 

MMS. 

Statistical Conservatism 

In addition to having conservatism in 

keff due to modeling practices, licensees 

may also provide conservatism in the 

statistical methods used to calculate the 

USL. For example, NUREG/CR–6698 

states that an acceptable method for 

calculating the bias is to use the singlesided tolerance limit approach with a 

95/95 confidence (i.e., 95% confidence 

that 95% of all future critical 

calculations will lie above the USL). If 

the licensee decides to use the singlesided tolerance limit approach with a 

95/99.9 confidence, this would result in 

a more conservative USL than with a 

95/95 confidence. This would be true of 

other methods for which the licensee’s 

confidence criteria exceeds the 

minimum accepted criteria. Generally, 

the NRC has accepted 95% confidence 

levels for validation results, so using 

more stringent confidence levels may 

provide conservatism. In addition, there 

may be other reasons a larger bias and/ 

or bias uncertainty than necessary has 

been used (e.g., because of the inclusion 

of inapplicable benchmark experiments 

that have a lower calculated keff). 

The reviewer may credit this 

conservatism towards having an 

adequate MoS if: (1) The licensee 

demonstrates that this translates into a 

specific Dkeff; and (2) the licensee 

demonstrates that the margin will be 

dependably present, based on license or 

other commitments. 

(3) Additional Risk-Informed 

Considerations 

Besides modeling conservatism and 

the validation results, other factors may 

provide added assurance of 

subcriticality. These factors should be 

considered in evaluating whether there 

is adequate MoS and are discussed 

below. 

System Sensitivity and Uncertainty 

The sensitivity of keff to changes in 

system parameters can be used to assess 

the potential effect of errors on the 

calculation of keff. If the calculated keff

is especially sensitive to a given 

parameter, an error in that parameter 

could have a correspondingly large 

contribution to the bias. Conversely, if 

keff is very insensitive to a given 

parameter, then an error may have a 

negligible effect on the bias. This is of 

particular importance when assessing 

whether the chosen critical experiments 

are sufficiently similar to applications to 

justify a small MMS. 

The reviewer should not consider the 

sensitivity in isolation, but should also 

consider the magnitude of uncertainties 

in the parameters. If keff is very sensitive 

to a given parameter, but the value of 

that parameter is known with very high 

accuracy (and its variations are wellcontrolled), the potential contribution to 

the bias may still be very small. Thus, 

the contribution to the bias is a function 

of the product of the keff sensitivity with 

the uncertainty. To illustrate this, 

suppose that keff is a function of a large 

number of variables, x1, x2,..., xN. Then 

the uncertainty in keff may be expressed 

as follows, if all the individual terms are 

independent: 

δ δ k k

x

x

i i

N

i

2

1

2

2 = ∂

∂





 



 =

∑

where the partial derivatives ∂k/∂xi are 

proportional to the sensitivity and the 

terms di represent the uncertainties, or 

likely variations, in the parameters. 

Each term in this equation then 

represents the contribution to the 

overall uncertainty in keff. 

There are several tools available to the 

reviewer to ascertain the sensitivity of 

keff to changes in the underlying 

parameters. Some of these are listed 

below: 

1. Analytical tools that calculate the 

sensitivity for each nuclide-reaction pair 

present in the problem may be used. 

One example of this is the TSUNAMI 

code in the SCALE 5 code package. 

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 reviewer should recognize that 

TSUNAMI only calculates the keff

sensitivity to changes in the underlying 

nuclear data, and not to other 

parameters that could affect the bias and 

should be considered. (See section on 

Benchmark Similarity for caveats about 

using TSUNAMI.) 

2. Direct sensitivity calculations may 

be used, in which system parameters are 

perturbed and the resulting impact on 

keff determined. Perturbation of atomic 

number densities can also be used to 

confirm the sensitivity calculated by 

other methods (e.g., TSUNAMI). Such 

techniques are not limited to 

considering the effect of the nuclear 

data. 

There are also several sources 

available to the reviewer to ascertain the 

uncertainty associated with the 

underlying parameters. For process 

parameters, these sources of uncertainty 

may include manufacturing tolerances, 

quality assurance records, and 

experimental and/or measurement 

results. For nuclear data parameters, 

these sources of uncertainty may 

include published data, uncertainty data 

distributed with the cross section 

libraries, or the covariance data used in 

methods such as TSUNAMI. 

Some systems are inherently more 

sensitive to changes in the underlying 

parameters than others. For example, 

high-enriched uranium systems 

typically exhibit a greater sensitivity to 

changes in system parameters (e.g., 

mass, moderation) than low-enriched 

systems. This has been the reason that 

HEU (i.e., >20wt% 235U) facilities have 

been licensed with larger MMS values 

than LEU (≤10wt% 235U) facilities. This 

greater sensitivity would also be true of 

weapons-grade Pu compared to lowassay mixed oxides (i.e., with a few 

percent Pu/U). However, it is also true 

that the uncertainties associated with 

measurement of the 235U cross sections 

are much smaller than those associated 

with measurement of the 238U cross 

sections. Both the greater sensitivity and 

smaller uncertainty would need to be 

considered in evaluating whether a 

larger MMS is needed for high-enriched 

systems. 


EN18OC05.014</MATH>
60572 Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 

Frequently, operating limits that are 

more conservative than safety limits 

determined using keff calculations are 

established to prevent those safety 

limits from being exceeded. For systems 

in which keff is very sensitive to the 

system parameters, more margin 

between the operating and safety limits 

may be needed. Systems in which keff is 

very sensitive to the process parameters 

may need both a larger margin between 

operating and safety limits and a larger 

MMS. This is because the system is 

sensitive to any change, whether it be 

caused by normal process variations or 

caused by unknown errors. Because of 

this, the assumption is often made that 

the MMS is meant to account for 

variations in the process or the ability 

to control the process parameters. 

However, the MMS is meant only to 

allow for unknown (or difficult to 

quantify) uncertainties in the 

calculation of keff. The reviewer should 

recognize that determination of an 

appropriate MMS is not dependent on 

the ability to control process parameters 

within safety limits (although both may 

depend on the system sensitivity). 

Some questions that the reviewer may 

ask in evaluating the system sensitivity 

as justification for the MMS 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? 

• Are the uncertainties associated 

with these underlying parameters wellknown? 

• How does the MMS compare to the 

expected magnitude of changes in keff

resulting from uncertainties in these 

underlying parameters? 

Knowledge of the Neutron Physics 

Another important consideration that 

may affect the appropriate MMS 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 MMS as systems where 

subcriticality is less certain. An example 

of a system known to be subcritical with 

high confidence is a light-water reactor 

fuel assembly. The design of these 

systems is such that they can only be 

made critical when highly thermalized. 

Due to extensive analysis and reactor 

experience, the flooded isolated 

assembly is known to be subcritical. In 

addition, the thermal neutron cross 

sections for materials in finished reactor 

fuel have been measured with a very 

high degree of accuracy (as opposed to 

cross sections in the resonance region). 

Other examples of systems in which 

there is independent corroborating 

evidence of subcriticality may include 

systems consisting of very simple 

geometric shapes, or other idealized 

situations, in which there is strong 

evidence that the system is subcritical 

based on comparison with highly 

similar systems in published sources 

(e.g., standards and handbooks). In these 

cases, the MMS may be significantly 

reduced due to the fact that the 

calculation of keff is not relied on alone 

to provide assurance of subcriticality. 

Reliance on independent knowledge 

that a given system is subcritical 

necessarily requires that the 

configuration of the system be fixed. If 

the configuration can change from the 

reference case, there will be less 

knowledge about the behavior of the 

changed system. For example, a finished 

fuel assembly is subject to strict quality 

assurance checks and would not reach 

final processing if it were outside of 

specifications. In addition, it has a form 

that has both been extensively studied 

and is highly stable. For these reasons, 

there is a great deal of certainty that this 

system is well-characterized and is not 

subject to change. A typical solution or 

powder system (other than one with a 

simple geometric arrangement) would 

not have been studied with the same 

level of rigor as a finished fuel 

assembly. Even if they were studied 

with the same level of rigor, these 

systems have forms that are subject to 

change into forms whose neutron 

physics has not been as extensively 

studied. 

Some questions that the reviewer may 

ask in evaluating the knowledge of the 

neutron physics as justification for the 

MMS 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, such that 

tolerances have been bounded? 

• Has the system been extensively 

studied in the nuclear industry and 

shown to be subcritical (e.g., in reactor 

fuel studies)? 

• Are there other reasons besides 

criticality calculations to conclude that 

the system will be subcritical (e.g., 

handbooks, standards, published data)? 

• How well-known is the nuclear data 

(e.g., cross sections) in the energy range 

of interest? 

Likelihood of the Abnormal Condition 

Some facilities been licensed with 

different sets of keff limits for normal 

and abnormal conditions. Separate keff

limits for normal and abnormal 

conditions are permissible but are not 

required. There is some likelihood that 

processes calculated to be subcritical 

will in fact be critical, and this 

likelihood increases as the MMS is 

reduced (though it cannot in general be 

quantified). NUREG–1718, ‘‘Standard 

Review Plan for the Review of an 

Application for a Mixed Oxide (MOX) 

Fuel Fabrication Facility,’’ states that 

abnormal conditions should be at least 

unlikely from the standpoint of the 

double contingency principle. Then, a 

somewhat higher likelihood that a 

system calculated to be subcritical is in 

fact critical is more permissible for 

abnormal conditions than for normal 

conditions, because of the low 

likelihood of the abnormal condition 

being realized. The reviewer should 

verify that the licensee has defined 

abnormal conditions such that 

achieving the abnormal condition 

requires at least one contingency to have 

occurred, that the system will be closely 

monitored so that it is promptly 

detected, and that it will be promptly 

corrected upon detection. It is also true 

that there is generally more 

conservatism present in the abnormal 

case, because the parameters that are 

assumed to have failed are analyzed at 

their worst-case credible condition. 

The increased risk associated with 

having a smaller MMS for abnormal 

conditions should be commensurate 

with and offset by the low likelihood of 

achieving the abnormal condition. That 

is, if the normal case keff limit is judged 

to be acceptable, then the abnormal case 

limit will also be acceptable, provided 

the increased likelihood (that a system 

calculated to be subcritical will be 

critical) is offset by the reduced 

likelihood of realizing the abnormal 

condition because of the controls that 

have been established. Note that if two 

or more contingencies must occur to 

reach a given condition, there is no 

requirement to ensure that the resulting 

condition is subcritical. If a single keff

limit is used (i.e., no credit for 

unlikelihood of the abnormal 

condition), then the limit must be found 

acceptable to cover both normal and 

credible abnormal conditions. The 

reviewer should always make this 

finding considering specific conditions 

and controls in the process(es) being 

evaluated. 

(4) Statistical Justification for the MMS 

The NRC does not consider statistical 

justification an appropriate basis for a 

specific MMS. Previously, some 

licensees have attempted to justify 

specific MMS values based on a 

comparison of two statistical methods. 

For example, the USLSTATS code 

issued with the SCALE code package 

Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60573 

contains two methods for calculating 

the USL: (1) the Confidence Band with 

Administrative Margin approach 

(calculating USL–1), and (2) the Lower 

Tolerance Band approach (calculating 

USL–2). The value of the MMS is an 

input parameter to the Confidence Band 

approach, but is not included explicitly 

in the Lower Tolerance Band approach. 

In this particular justification, adequacy 

of the MMS is based on a comparison 

of USL–1 and USL–2 (i.e., the condition 

that USL–1, including the chosen MMS, 

is less than USL–2). However, the 

reviewer should not accept this 

justification. 

The condition that USL–1 (with the 

chosen MMS) is less than USL–2 is 

necessary, but is not sufficient, to show 

that an adequate MMS has been used. 

These methods are both statistical 

methods, and a comparison can only 

demonstrate whether the MMS is 

sufficient to bound any statistical 

uncertainties included in the Lower 

Tolerance Band approach but not 

included in the Confidence Band 

approach. There may be other statistical 

or systematic errors in calculating keff

that are not included in either statistical 

treatment. Because of this, an MMS 

value should be specified regardless of 

the statistical method used. Therefore, 

the reviewer should not consider such 

a statistical approach an acceptable 

justification for any specific value of the 

MMS. 

(5) Summary 

Based on a review of the licensee’s 

justification for its chosen MMS, taking 

into consideration the aforementioned 

factors, the staff should make a 

determination as to whether the chosen 

MMS provides reasonable assurance of 

subcriticality under normal and credible 

abnormal conditions. The staff’s review 

should be risk-informed, in that the 

review should be commensurate with 

the MoS and should consider the 

specific facility and process 

characteristics, as well as the specific 

modeling practices used. As an 

example, approving an MMS value 

greater than 0.05 for processes typically 

encountered in enrichment and fuel 

fabrication facilities should require only 

a cursory review, provided that an 

acceptable validation has been 

performed and modeling practices at 

least as conservative as those in 

NUREG–1520 have been utilized. The 

approval of a smaller MMS will require 

a somewhat more detailed review, 

commensurate with the MMS that is 

requested. However, the MMS should 

not be reduced below 0.02 due to 

inherent uncertainties in the cross 

section data and the magnitude of code 

errors that have been discovered. 

Quantitative arguments (such as 

modeling conservatism) should be used 

to the extent practical. However, in 

many instances, the reviewer will need 

to make a judgement based at least 

partly on qualitative arguments. The 

staff should document the basis for 

finding the chosen MMS value to be 

acceptable or unacceptable in the SER, 

and should ensure that any factors upon 

which this determination rests are 

ensured to be present over the facility 

lifetime (e.g., through license 

commitment or condition). 

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 MMS is 

strongly dependent upon specific 

processes, conditions, and calculational 

practices at the facility being licensed. 

Judgement and experience must be 

employed in evaluating the adequacy of 

the proposed MMS. In the past, an MMS 

of 0.05 has generally been found 

acceptable for most typical lowenriched fuel cycle facilities without a 

detailed technical justification. A 

smaller MMS may be acceptable but 

will require some level of technical 

review. However, for reasons stated 

previously, the MMS should not be 

reduced below 0.02. 

An MMS of 0.05 should be found 

acceptable for low-enriched fuel cycle 

processes and facilities if: 

1. A validation has been performed 

that meets accepted industry guidelines 

(e.g., meets the requirements of ANSI/ 

ANS–8.1–1998, NUREG/CR–6361, and/ 

or NUREG/CR–6698). 

2. There is an acceptable number of 

benchmark experiments with similar 

geometric forms, material compositions, 

and neutron energy spectra to 

applications. These experiments cover 

the range of parameters of applications, 

or else margin is provided to account for 

extensions to the AOA. 

3. The processes to be evaluated 

include materials and process 

conditions similar to those that occur in 

low-enriched fuel cycle applications 

(i.e., no new fissile materials, unusual 

moderators or absorbers, or technologies 

new to the industry that can affect the 

types of systems to be modeled). 

The reviewer should consider any 

factors, including those enumerated in 

the discussion above, that could result 

in applying additional margin (i.e., a 

larger MMS) or may justify reducing the 

MMS. The reviewer must then exercise 

judgement in arriving at an MMS that 

provides for adequate assurance of 

subcriticality. 

Some of the factors that may serve to 

justify reducing the MMS include: 

1. There is a predictable and 

dependable amount of conservatism in 

modeling practices, in terms of keff, that 

is assured to be maintained (in both 

normal and abnormal conditions) over 

the facility lifetime. 

2. Benchmark experiments have 

nearly identical geometric forms, 

material compositions, and neutron 

energy spectra to applications, and the 

validation is specific to this type of 

application. 

3. The validation methodology 

substantially exceeds accepted industry 

guidelines (e.g., it uses a very 

conservative statistical approach, 

considers an unusually large number of 

trending parameters, or analyzes the 

bias for a large number of subgroups of 

critical experiments). 

4. The system keff is demonstrably 

much less sensitive to uncertainties in 

cross sections or variations in other 

system parameters than typical lowenriched fuel cycle processes. 

5. There is reliable information 

besides results of calculations that 

provides assurance that the evaluated 

applications will be subcritical (e.g., 

experimental data, historical evidence, 

industry standards or widely-accepted 

handbooks). 

6. The MMS is only applied to 

abnormal conditions, which are at least 

unlikely to be achieved, based on 

credited controls. 

Some of the factors that may 

necessitate increasing (or not approving) 

the MMS include: 

1. The technical practices employed 

by the licensee are less conservative 

than standard industry modeling 

practices (e.g., do not adequately bound 

reflection or the full range of credible 

moderation, do not take geometric 

tolerances into account). 

2. There are few similar critical 

experiments of benchmark quality that 

cover the range of parameters of 

applications. 

3. The validation methodology 

substantially falls below accepted 

industry guidelines (e.g., it uses less 

than a 95% confidence in the statistical 

approach, fails to consider trends in the 

bias, fails to account for extensions to 

the AOA). 

60574 Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 

4. The validation results otherwise 

tend to cast doubt on the accuracy of the 

bias and its uncertainty (i.e., the critical 

experiments are not normally 

distributed, there is a large number of 

outliers discarded (≥2%), there are 

distinct subgroups of experiments with 

lower keff than the experiments as a 

whole, trending fits do not pass 

goodness-of-fit tests, etc.). 

5. The system keff is demonstrably 

much more sensitive to uncertainties in 

cross sections or other system 

parameters than typical low-enriched 

fuel cycle processes. 

6. There is reliable information that 

casts doubt on the results of the 

calculational method or the 

subcriticality of evaluated applications 

(e.g., experimental data, reported 

concerns with the nuclear data). 

The purpose of asking the questions 

in the individual discussion sections is 

to ascertain the degree to which these 

factors either provide justification for 

reducing the MMS or necessitate 

increasing the MMS. These lists are not 

all-inclusive, and any other technical 

information that demonstrates the 

degree of confidence in the calculational 

method should be considered. 

Recommendation 

The guidance in this ISG should 

supplement the current guidance in the 

nuclear criticality safety chapters of the 

fuel facility SRPs (NUREG–1520 and 

–1718). However, NUREG–1718, Section 

6.4.3.3.4, states that the licensee should 

submit justification for the MMS, but 

then states that an MMS 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 two 

statements are inconsistent. Therefore, 

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 

ANSI/ANS–8.1–1998, ‘‘Nuclear 

Criticality Safety in Operations with 

Fissionable Materials Outside Reactors,’’

American Nuclear Society. 

ANSI/ANS–8.17–1984 (R1997), 

‘‘Criticality Safety Criteria for the 

Handling, Storage, and Transportation 

of LWR [Light Water Reactor] Fuel 

Outside Reactors,’’ American Nuclear 

Society. 

IN 2005–13, ‘‘Potential NonConservative Error in Modeling 

Geometric Regions in the KENO–V.a 

Criticality Code,’’ May 17, 2005. 

U.S. Nuclear Regulatory Commission 

(U.S.) (NRC). NUREG–1520, ‘‘Standard 

Review Plan for the Review of a License 

Application for a Fuel Cycle Facility.’’

NRC: Washington, DC March 2002. 

U.S. Nuclear Regulatory Commission 

(U.S.) (NRC). NUREG–1718, ‘‘Standard 

Review Plan for the Review of an 

Application for a Mixed Oxide (MOX) 

Fuel Fabrication Facility.’’ NRC: 

Washington, DC August 2000. 

U.S. Nuclear Regulatory Commission 

(U.S.) (NRC). NUREG/CR–6698, ‘‘Guide 

for Validation of Nuclear Criticality 

Safety Calculational Methodology.’’

NRC: Washington, DC January 2001. 

U.S. Nuclear Regulatory Commission 

(U.S.) (NRC). NUREG/CR–6361, 

‘‘Criticality Benchmark Guide for LightWater-Reactor Fuel in Transportation 

and Storage Packages.’’ NRC: 

Washington, DC March 1997. 

Approved: llll Date: ll 

Director, Division of Fuel Cycle Safety and 

Safeguards, NMSS 

Appendix A—ANSI/ANS–8.17 

Calculation of Maximum keff

ANSI/ANS–8.17–1984 (R1997), ‘‘Criticality 

Safety Criteria for the Handling, Storage, and 

Transportation of LWR Fuel Outside 

Reactors,’’ contains a detailed discussion of 

the various factors that should be considered 

in setting keff limits. This is consistent with, 

but more detailed than, the discussion in 

ANSI/ANS–8.1–1998. 

The subcriticality criterion from Section 

5.1 of ANSI/ANS–8.17–1984 (R1997) is: 

ks ≤ kc ¥ Dks ¥ Dkc ¥ Dkm

where ks is the calculated keff corresponding 

to the application, Dks is its uncertainty, kc

is the mean keff resulting from the calculation 

of critical experiments, Dkc is its uncertainty, 

and Dkm is the MMS. The types of 

uncertainties included in each of these 

‘‘delta’’ terms is provided, and includes the 

following: 

Dks = (1) Statistical uncertainties in 

computing ks; (2) convergence uncertainties 

in computing ks, (3) material tolerances; (4) 

fabrication tolerances; (5) uncertainties due 

to limitations in the geometric representation 

used in the method; and (6) uncertainties due 

to limitations in the material representations 

used in the method. 

Dkc = (7) uncertainties in the critical 

experiments; (8) statistical uncertainties in 

computing kc; (9) convergence uncertainties 

in computing kc; (10) uncertainties due to 

extrapolating kc outside the range of 

experimental data; (11) uncertainties due to 

limitations in the geometric representations 

used in the method; and (12) uncertainties 

due to limitations in the material 

representations used in the method. 

Dkm = an allowance for any additional 

uncertainties (MMS). 

To the extent that not all 12 sources of 

uncertainty listed above have been explicitly 

taken into account, they may be allowed for 

by increasing the value of Dkm. The more of 

these sources of uncertainty that have been 

taken into account, the smaller the necessary 

additional margin Dkm. As a general 

principle, however, the MMS should be large 

compared to known uncertainties in the 

nuclear data and limitations of the 

methodology. However, a value of the MMS 

below 0.02 should not be used. 

Frequently, the terms in the above equation 

relating to the application are grouped on the 

left-hand side of the equation, so that the 

equation is rewritten as follows: 

ks + Dks ≤ kc ¥ Dkc ¥ Dkm

where the terms on the right-hand side of the 

equation are often lumped together and 

termed the Upper Subcritical Limit (USL), so 

that the USL = kc ¥ Dkc¥ Dkm. 

Relation to the Minimum Subcritical Margin 

(MMS) 

The MoS has been defined as the 

difference between the actual value of keff

and the value of keff at which the system is 

expected to be critical. The expected (best 

estimate) critical value of keff is the mean keff

value of all critical experiments analyzed 

(bias), including consideration of the 

uncertainty in the bias (i.e., kc¥Dkc). The 

calculated value of keff for an application 

generally exceeds the actual (physical) keff

value due to conservative assumptions in 

modeling the system. In terms of the above 

USL equation, the MoS may be expressed 

mathematically as: 

MoS = kc ¥ Dkc ¥ (ks ¥ Dksa) ¥ Dks

where the term in parentheses is equal to the 

actual (physical) keff of the application, ksa. 

A term, Dksa, has been added to represent the 

difference between the actual and calculated 

value of keff for the application (i.e., Dksa = 

change in keff resulting from modeling 

conservatism). In terms of the USL: 

MoS = USL + Dkm ¥ks + Dksa ¥ Dks

The minimum allowed value of the MoS is 

reached when the calculated keff for the 

application, ks + Dks, is equal to the USL. 

When this occurs, the minimum value of the 

MoS is: 

MoS ≥ Dkm + Dksa

Thus, adequate margin (MoS) may be 

assured either by conservatism in modeling 

practices or in the explicit specification of 

Dkm (MMS). This is discussed in the ISG 

section on modeling conservatism. 

Glossary 

Application: calculation of a fissionable 

system in the facility performed to 

demonstrate subcriticality under normal or 

credible abnormal conditions. 

Area of applicability: the ranges of material 

compositions and geometric arrangements 

within which the bias of a calculational 

method is established. 

Benchmark experiment: a critical 

experiment that has been peer-reviewed and 

published and is sufficiently well-defined to 

be used for validation of calculational 

methods. 

Bias: a measure of the systematic 

differences between calculational method 

results and experimental data. 

Federal Register / Vol. 70, No. 200 / Tuesday, October 18, 2005 / Notices 60575 

Bias uncertainty: a measure of both the 

accuracy and precision of the calculations 

and the uncertainty in the experimental data. 

Calculational method: includes the 

hardware platform, operating system, 

computer algorithms and methods, nuclear 

reaction data, and methods used to construct 

computer models. 

Critical experiment: a fissionable system 

that has been experimentally determined to 

be critical (with keff ≈ 1). 

Margin of safety: the difference between 

the actual value of a parameter and the value 

of the parameter at which the system is 

expected to be critical with critical defined 

as keff = 1 = bias = bias uncertainty. 

Margin of subcriticality (MoS): the 

difference between the actual value of keff

and the value of keff at which the system is 

expected to be critical with critical defined 

as keff = 1 = bias = bias uncertainty. 

Minimum margin of subcriticality (MMS): a 

minimum allowed margin of subcriticality, 

which is an allowance for any unknown 

uncertainties in calculating keff. 

Subcritical limit: the bounding value of a 

controlled parameter under normal case 

conditions. 

Upper subcritical limit (USL): the 

maximum allowed value of keff (including 

uncertainty in keff), under both normal and 

credible abnormal conditions, including 

allowance for the bias, the bias uncertainty, 

and a minimum margin of subcriticality. 

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