Initial Assessment of 

Uncertainties Associated with 

BADGER Methodology 

Manuscript Completed: September 2012 

Date Published: September 2012 

Prepared by 

J. A. Chapman and J. M. Scaglione 

Oak Ridge National Laboratory 

Managed by UT-Battelle, LLC 

Oak Ridge, TN37831-6170 

A. Pulvirenti, NRC Project Manager 

M. Aissa, NRC Technical Monitor 

Prepared for 

Division of Engineering 

Office of Nuclear Regulatory Research 

U. S. Nuclear Regulatory Commission 

Washington, DC20555-0001 

NRC Job Code V6243 

i 

FOREWORD 

The degradation of neutron absorbing materials in spent fuel pools has prompted the staff to undertake a 

review of the tools and methods used by the industry to ascertain the condition of panels. Boraflex and 

Carborundum have degraded severely through chemically-induced changes and dissolution. Boral® has 

degraded by corrosion and deformation. Consequently, the subcriticality margins that existed when 

neutron absorbers were first installed have decreased. As margins decrease, one must have confidence in 

the neutron absorber data used in criticality analyses to demonstrate compliance with the subcriticality 

requirements specified by Title 10 of the Code of Federal Regulations Section 50.68 (10 CFR 50.68) or 

General Design Criteria (GDC) 62. Therefore, when using surveillance methods to determine the areal 

density of neutron absorbers in spent fuel pools, it is necessary that associated uncertainties be catalogued 

in a systematic manner. 

The staff has focused on the surveillance methods for neutron absorber panels. Specifically, the staff has 

undertaken a review of the Boraflex rack life extension computer code (RACKLIFE) and the Boron Areal 

Density Gauge for Evaluating Racks (BADGER) in-situ measurement technique. The primary focus of 

this report is the uncertainty associated with the BADGER in-situ instrument. The uncertainty associated 

with RACKLIFE is discussed in the companion report:RACKLIFE, and BADGER: Description and 

Uncertainties (T. C. Haley). 

The BADGER system was originally designed, assembled, and tested in the early-to-mid 1990s by 

Northeast Technologies Company (NETCO, now a subsidiary of Curtiss-Wright), as a nondestructive 

scoping tool to evaluate neutron absorbers placed in spent fuel racks. While BADGER is employed 

primarily to measure the degradation of Boraflex neutron absorbing material, it is theoretically applicable 

to any neutron absorber and has, in fact, been used for the phenolic matrix absorber Carborundum. 

The analysis and assessment of the BADGER instrument and the associated measurement methodology 

yielded three principal findings. First, detailed documentation is required in order to conduct a rigorous 

quantitative uncertainty analysis. This includes technical specifications and/or quality control test reports. 

For BADGER, such documentation is not publicly available nor was it available to the authors of this 

report. Therefore, a Type B analysis, as defined by National Institute for Standards and Testing for use in 

cases where supporting measurement data is not available, was conducted. Estimates of uncertainty that 

appear in this report are a combination of data, analytical estimates and expert opinions. 

Secondly, although the Type B analysis did not provide quantitative estimates for each contributor to 

overall uncertainty, several contributors to uncertainty were identified that can potentially invalidate 

measurement results. Examples of such errors are use of the instrument in a very high gamma field, the 

improper adjustment of low-level pulse discrimination, inconsistency in operator interpretation of data, 

and material mismatch between calibration and test panel. Flux-trap racks, a configuration where two 

neutron absorber panels are interposed between spent fuel assemblies, are especially susceptible to high 

error because neutrons must travel through two panels to the detector. 

Lastly, head misalignment could contribute an estimated uncertainty of ±40 percent to the overall 

BADGER results. The uncertainty resulting when the source and detector head are not properly aligned 

was estimated using the MAVRIC neutron radiation transport sequence in the SCALE criticality package. 

This 40 percent error may be significantly higher if the rack cell walls are warped or deformed. 

Uncertainties associated with over 40 different factors affecting the measurement accuracy of the 

BADGER system were assessed, but documented information was available for less than five. In 

addition to discussing contributors to uncertainty, this report provides examples of the types of data and 

information necessary for a more rigorous calculation of uncertainty. The report illustrates the need to 
ii 

more closely scrutinize actual information and data associated with BADGER campaigns, and quantify 

uncertainties that propagate in criticality calculations. 
iii 

EXECUTIVE SUMMARY 

This report documents the review of the design, use, and implementation of BADGER,*

 the Boron-10 

Areal Density Gauge for Evaluating Racks. The review was specifically intended to understand the 

magnitude of the uncertainties involved in the application of the methodology for evaluating spent-fuelpool neutron absorber panels. BADGER is a nondestructive test (NDT) instrument that measures neutron 

transmission through interposing panels of light water reactor (LWR) spent fuel racks between a 252Cf 

neutron source and four boron trifluoride (BF3) neutron detectors. The neutron transmission measurement 

is used to characterize the physical properties of the neutron absorber panels. While originally designed 

for the measurement of Boraflex, BADGER has also been used in conjunction with other neutronabsorbing materials. Measurement results are used by licensees to demonstrate, in part, compliance with 

Title 10 CFR 50.68, Criticality Accident Requirements. 

BADGER uses BF3 gas-filled detectors. Gas-filled detectors were among the first devices used for 

radiation detection. While BF3 tubes have been used in many neutron detection applications, their use for 

measuring areal density of 10B in situ in spent fuel pool neutron absorber panels can be challenging. BF3

detectors tend to be reliable and offer good neutron/gamma-ray discrimination at a reasonable efficiency. 

The interaction probability for gamma-rays is relatively low (typically orders of magnitude lower than 

thermal neutron interaction probabilities) when the device is used in acceptable gamma environments, and 

when the detector and electronics have been selected properly to accommodate the upper range of 

gamma-ray dose rates to be encountered. For measurements in a spent fuel pool, where high gamma-ray 

fluxes (~1000 R/hr) may be encountered, the gamma-ray sensitivity of the detector may dominate all 

other considerations. 

In the course of conducting the uncertainty assessment, it was found that no information was available 

regarding specific performance testing of the device to identify and evaluate sources of error. It was also 

found that BADGER testing has been conducted in a heuristic manner (example inferences provided in 

Section 2) since its inception as measurement campaigns encountered different spent fuel pool rack 

designs and introduced new information that needed to be accounted for in the overall test protocol. 

However, the original demonstration measurement results†

 do not account for many of the engineering 

deployment uncertainties that arise in practice for in situ measurements. As a result, a Type B uncertainty 

analysis was conducted in accordance with NIST Technical Note 1297,‡

 such that estimates of uncertainty 

are provided on the basis of many years of experience conducting neutron measurements, and writing 

American National Standards Institute (ANSI), American Society for Testing and Materials (ASTM), 

International Standards Organization (ISO), and International Electrotechnical Commission (IEC) 

standards on the conduct of radiation measurements for nondestructive assay (NDA) and NDT systems. 

A summary listing of parameters that can impact the measurement performance of BADGER was 

documented in this report and is presented in Section 6. Each of the individual parameters was grouped 

into categories reflecting different aspects of the BADGER system and how the results are used. Because 

 *

BADGER: Boron-10 Areal Density Gauge for Evaluating Racks, developed by Northeast Technology 

Corporation for the Electric Power Research Institute (EPRI). 

†

Electric Power Research Institute (EPRI), “BADGER, A Probe for Nondestructive Testing of Residual Boron10 Absorber Density in Spent Fuel Storage Racks: Development and Demonstration,” TR-107335, EPRI, Palo Alto, 

CA, October 1997. 

‡

National Institute of Standards and Technology, “Guidelines for Evaluating and Expressing the Uncertainty of 

NIST Measurement Results,” United States Department of Commerce, Technology Administration, National 

Institute of Standards and Technology (NIST), Technical Note 1297, 1994. 
iv 

of limitations and constraints affiliated with obtaining test reports, procurement specifications, technical 

specifications, and operating procedures (including those for quality control), uncertainties of individual 

components cannot be quantified nor combined in any scientifically defensible manner, with the 

information available to the authors. As such, no justification can be made for an estimate of total 

measurement uncertainty for the BADGER system. Monte Carlo radiation transport calculations 

documented in Appendix A show that the influence of individual parameters could be in excess of ±40 

percent each on reported average areal densities. Thus, the total uncertainty stemming from all the 

different sources examined in this report could be much greater. 

 
v 

CONTENTS 

Page

FOREWORD ................................................................................................................................................. i

EXECUTIVE SUMMARY ......................................................................................................................... iii

LIST OF FIGURES ..................................................................................................................................... ix

LIST OF TABLES ....................................................................................................................................... xi

ACKNOWLEDGMENTS ......................................................................................................................... xiii

LIST OF ACRONYMS AND UNITS ........................................................................................................ xv

1 INTRODUCTION ................................................................................................................................... 1

2 BACKGROUND ..................................................................................................................................... 3

3 METHOD OF REVIEW ........................................................................................................................ 10

4 BADGER SYSTEM DESCRIPTION ................................................................................................... 12

4.1 SOURCE/DETECTOR MODULES ............................................................................................. 13

4.2 DRIVE SYSTEM .......................................................................................................................... 14

4.3 NUCLEAR ELECTRONICS ......................................................................................................... 14

4.4 DATA ACQUISITION AND CONTROL COMPUTER.............................................................. 14

5 BADGER SYSTEM DISCUSSION AND RELEVANT OBSERVATIONS ON UNCERTAINTY ... 15

5.1 NEUTRON SOURCE .................................................................................................................... 16

5.1.1 Count Rate .......................................................................................................................... 16

5.1.2 Source Strength and Decay ................................................................................................ 17

5.1.3 Neutron Moderation by Covers on Heads .......................................................................... 17

5.2 DETECTOR CHARACTERISTICS ............................................................................................. 17

5.2.1 Size ..................................................................................................................................... 18

5.2.2 Efficiency ........................................................................................................................... 18

5.2.3 Fill Gas Pressure ................................................................................................................. 18

5.2.4 10B Enrichment of the Gas .................................................................................................. 19

5.2.5 Aging of BF3 Detectors ...................................................................................................... 19

5.2.6 Detector Wall Material ....................................................................................................... 19

5.3 INTERFERENCE .......................................................................................................................... 20

5.3.1 Background Neutron Flux from Surrounding Assemblies ................................................. 20

5.3.2 Gamma Interference ........................................................................................................... 20

5.4 ELECTRONICS ............................................................................................................................ 21

5.4.1 EMI Susceptibility .............................................................................................................. 22
vi 

CONTENTS (continued) 

Page

5.4.2 RF Pickup ........................................................................................................................... 22

5.4.3 Amplifiers, Discriminators, Power Supply, Acquisition Board ......................................... 22

5.4.4 Signal Processors ................................................................................................................ 22

5.4.5 Discriminators for Pileup Rejection, Wall Effect ............................................................... 23

5.4.6 Dead Time .......................................................................................................................... 23

5.5 APPARATUS GEOMETRY ......................................................................................................... 23

5.5.1 Head Misalignment ............................................................................................................ 24

5.5.2 Rack Cell Fit ....................................................................................................................... 26

5.5.3 Compression Springs, Shims, Vertical Offsets .................................................................. 26

5.5.4 Effect of Rack Cell Deformation: Panel Cladding Bulges, Collisions with Assemblies ... 26

5.5.5 Determination of Detector Coverage of Panel Area ........................................................... 26

5.6 CALIBRATION ............................................................................................................................ 27

5.6.1 Number, Range, and Precision of 10B Areal Density of Standard Panels ........................... 27

5.6.2 Standard Panel Degradation ............................................................................................... 28

5.6.3 Adjustment of Calibration Procedure for Specific Pool Characteristics ............................ 28

5.6.4 Relevance of Standard Panel Material to Rack Panel Material .......................................... 29

5.6.5 Location and Acclimatization of Calibration Cell in Pool ................................................. 30

5.6.6 Choice of “Zero-Loss” Panel and Uncertainty of Actual 10B Areal Density ...................... 30

5.6.7 Nonlinearity of Calibration Curve, Especially as Applied to Flux-Trap Racks ................. 32

5.6.8 Uncertainties in Calibration Slope, Especially as Applied to Flux-Trap Racks ................. 32

5.6.9 Frequency of Calibration during a BADGER Campaign ................................................... 34

5.6.10 Confirmatory Analysis with Destructive Examination ...................................................... 34

5.6.11 Panel-Specific Use and Interpretation of Unattenuated Region Data................................. 35

5.6.12 Algorithms to Convert BADGER Trace Data into Input for Calibration Curve ................ 36

5.7 DATA PROCESSING ................................................................................................................... 37

5.7.1 Reliance on Operator Experience to Detect and Characterize Heterogeneous 

 Degradation ........................................................................................................................ 37

5.7.2 Applicability of Boraflex-Based Algorithms to Non-Boraflex Material Such 

 as Boral® or Metamic ......................................................................................................... 39

5.7.3 Feedback Procedure ............................................................................................................ 39

5.8 STATISTICAL EXTRAPOLATION AND SURVEILLANCE FREQUENCY .......................... 40

5.8.1 Choice of Test Panels to Survey ......................................................................................... 40
vii 

CONTENTS (continued) 

Page

5.8.2 Lack of Duplicate Scans of the Same Test Panel ............................................................... 40

5.8.3 Application of Results of Selected Panels to Entire Pool ................................................... 41

5.8.4 Frequency of BADGER Campaigns, Especially for Panel Materials Where 

 Intermediate Calculational Methods Such As RACKLIFE Are Unavailable ..................... 42

5.8.5 Application of Final Output to Criticality Analyses of Record .......................................... 42

5.8.6 Use of Final Output in Abnormal or Accident Sequence Criticality Analyses .................. 43

6 SUMMARY ........................................................................................................................................... 45

7 CONCLUSION...................................................................................................................................... 58

8 REFERENCES ...................................................................................................................................... 60

APPENDIX A ........................................................................................................................................... A-1

APPENDIX B ........................................................................................................................................... B-1

APPENDIX C ........................................................................................................................................... C-1
viii 

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ix 

LIST OF FIGURES 

Page

Figure 2.1. Typical spent fuel pool for U.S. nuclear power plant. ........................................................... 4

Figure 2.2. Typical Region I spent fuel pool rack configuration. ............................................................ 5

Figure 2.3. Typical Region II spent fuel pool rack configuration ............................................................ 5

Figure 2.4. Degraded Boraflex ................................................................................................................. 6

Figure 4.1. Axial cross-section depiction of BADGER in operation in a spent fuel pool ..................... 12

Figure 4.2. Figure showing close proximity of source to absorber material and neutron 

detectors (BWR BADGER system). ................................................................................... 13

Figure 5.1. BF3 circuit diagram. ............................................................................................................. 21

Figure 5.2. Detector probe orientation ................................................................................................... 25

Figure 5.3. Representative calibration curve. ........................................................................................ 34

Figure 5.4. Representative Region II spent fuel pool storage cell ......................................................... 35

Figure 5.5. BADGER detector traces .................................................................................................... 38

Figure A.1. Cutaway view of representative Region II BWR storage rack model. .............................. A-3

Figure A.2. Areal density calibration curve for optimum source and detector head 

orientation positioning. ...................................................................................................... A-4

Figure A.3. Source and detector head positioning with 3° twist misalignment for detector head. ....... A-5

Figure A.4. Source and detector head positioning with a 0.66-cm probe center-to-center offset 

misalignment. .................................................................................................................... A-5

Figure A.5. Change in recorded areal density due to twist misalignment. ........................................... A-6

Figure A.6. Change in recorded areal density due to offset misalignment. .......................................... A-7

 
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xi 

LIST OF TABLES 

Page

Table 5-1. Example calibration cell data .............................................................................................. 33

Table 6-1. Summary table of measurement system sources of uncertainty .......................................... 47

Table A-1. Relative change in areal density due to twist misalignment .............................................. A-6

Table A-2. Relative change in areal density due to offset misalignment ............................................ A-7

Table B-1. MAVRIC-generated optimum orientation configuration results ....................................... B-2

Table B-2. MAVRIC-generated twist misalignment configuration results ......................................... B-3

Table B-3. MAVRIC generated offset misalignment configuration results ........................................ B-4
xii 

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xiii 

ACKNOWLEDGMENTS 

This work was performed under contract with the U.S. Nuclear Regulatory Commission (NRC) Office of 

Nuclear Regulatory Research. The authors thank A. Pulvirenti and J. Barr, the NRC Project Managers; 

M. Aissa, M. Gavrilas, and C. Harris of the Office of Nuclear Regulatory Research (RES); E. Wong and 

K. Wood of the Office of Nuclear Reactor Regulation (NRR); and Dr. Thomas Haley (consultant) for 

their support and guidance. Many valuable review comments were received from NRC staff members. 

The authors also wish to thank D. E. Mueller and B. J. Marshall for their reviews and D. J. Weaver and 

D. P. Stevens for assistance in formatting and preparation of the final document. 
xiv 

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xv 

LIST OF ACRONYMS AND UNITS 

ANSI 

ASTM 

BADGER 

Boraflex 

10B areal density 

BWR 

CE 

CFR 

EMI 

EPRI 

GDC 

GUM 

IEC 

IEEE 

IN 

ISO 

LLD 

LWR 

MSE 

NDA 

NDT 

NETCO 

NIM 

NIST 

NRC 

PWR 

QC 

RACKLIFE 

RF 

SCA 

TC 

TMU 

TTL 

UL 

ULD 

American National Standards Institute 

American Society for Testing and Materials 

Boron-10 Areal Density Gauge for Evaluation of Racks 

a silicon-based composite of the neutron absorber, boron-10 

density thickness (g*cm-2) of boron-10 in neutron absorbers 

boiling water reactor 

CE certification refers to products eligibility to be sold in European Union 

Code of Federal Regulations 

electromagnetic interference 

Electric Power Research Institute 

general design criterion 

guide to the expression of uncertainty in measurement 

International Electrotechnical Commission 

Institute of Electrical and Electronics Engineers 

information notice 

International Standards Organization 

lower level discriminator 

light water reactor 

mean square error 

nondestructive assay 

nondestructive testing 

Northeast Technology Corporation 

nuclear instrumentation module 

National Institute of Standards and Technology 

Nuclear Regulatory Commission 

pressurized water reactor 

quality control 

Boraflex Rack Life Extension Computer Code 

radio frequency 

single channel analyzer 

Tennelec Corporation 

total measurement uncertainty 

transistor-transistor logic 

Underwriters Laboratories 

upper level discriminator 

 
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1 

1 INTRODUCTION 

Criticality safety analyses are performed to demonstrate that a proposed fuel storage configuration meets 

the applicable requirements of Title 10 of the Code of Federal Regulations (CFR) Part 50.68, “Criticality 

accident requirements,” (Reference 1) and Part 50 Appendix A General Design Criterion (GDC) 62, 

“Prevention of criticality in fuel storage and handling” (Reference 2). Several options for criticality 

control are available to licensees including use of a geometrically safe configuration, soluble boron, and 

interstitial neutron absorber panels. As spent fuel pool strategies shift to maximizing storage density, 

reliance on neutron absorber panel reactivity control has increased. Utilities have typically used neutron 

absorbers such as Boraflex, Boral®, MetamicTM, and Carborundum in spent-fuel storage racks to control 

reactivity where boron-10 (10B) is the principal neutron-absorbing material contained in the plate. 

Neutron-absorbing materials used in spent fuel pools and credited to demonstrate compliance with NRC 

regulations are exhibiting degradation, as documented in Information Notices (INs) 87-43, 93-70, 95-38, 

and 2009-26 and Generic Letter (GL) 96-04 (References 3, 4, 5, 6, and 7). As discussed in Reference 6, a 

position has been taken that the degradation mechanisms and deformation rates of any of the neutronabsorbing materials in the spent fuel pool are not well understood. Therefore, licensees that credit the use 

of a neutron-absorbing material to maintain subcriticality in their spent fuel pool must monitor it for any 

indications that degradation of the material may be occurring that can result in noncompliance with 

criticality requirements for spent fuel pools. 

A nondestructive measurement system was developed by Northeast Technology Corp. for the Electric 

Power Research Institute (EPRI), named BADGER (Boron-10 Areal Density Gage for Evaluating Racks) 

(Reference 8). The BADGER system is being used by utilities to monitor and estimate the extent of 

degradation of the neutron absorber panels to determine whether sufficient absorber remains to meet 

subcriticality margin requirements. BADGER is used to measure neutron transmission in 2-inch 

increments up the vertical length of a rack cell wall in a spent fuel pool. Through calibration and the use 

of various algorithms, the neutron transmission measurement is converted to a 10B areal density estimate. 

The purpose of this report is to provide a technical assessment of the BADGER system surveillance tool, 

for both pressurized water reactor (PWR) and boiling water reactor (BWR) rack designs, in an effort to 

understand the magnitude of the uncertainties as well as any limitations in its methodology and 

application. In particular, this report reviews the implementation of the BADGER system in measuring 

neutron transmission, correlating neutron count rates to absorber areal density, and determining how this 

information is applied to criticality evaluations of spent fuel pools, and identifies parameters that 

contribute most to uncertainty. Uncertainties considered include the use of the instrument in a very high 

gamma field, the improper adjustment of low-level pulse discrimination, inconsistency in operator 

interpretation of data, and material mismatch between calibration and test panel. The terms “error” and 

“uncertainty” are used throughout this document. The statistical definitions and usage of these two terms 

may have different interpretations. However, the major point of this document is to identify issues which 

may cause measurement deviation from a true value, whether or not the issues are termed errors or 

uncertainties. 

Though most of the test data information reviewed and examples provided are from Boraflex evaluations, 

the overall assessment is being conducted in terms of general applicability independent of the specific 

neutron absorber material used in the spent fuel pool rack. 
2 

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3 

2 BACKGROUND 

Neutron absorbers for spent fuel pool racks are typically composed of a neutron absorber nuclide within a 

matrix that maintains the distribution of the absorber material. Both metal matrix and non-metal-matrix 

neutron absorber materials have been produced and are currently being used for spent fuel pool 

applications. The Handbook of Neutron Absorber Materials for Spent Nuclear Fuel Transportation and 

Storage Applications (Reference 9) provides a listing of data and product information for a number of 

metal matrix neutron absorbers that are commercially available and have had the most widespread use in 

spent fuel storage and transportation applications, as well as information on non-metal-matrix absorbers, 

newly proposed aluminum matrix composites, and emerging materials. The primary function of the 

neutron absorber is to provide sufficient thermal neutron removal along the active fuel region between 

adjacent fuel assemblies. 

Spent fuel pools that employ absorber panels may consist of one of two types of rack systems (or a 

combination of the two)—(1) flux trap or Region I systems, which contain two absorber panels separated 

by a water gap between panels, and (2) higher-density, egg-crate or Region II systems, where only a 

single absorber panel is interstitial to the spent fuel assemblies. A photograph of a typical spent fuel pool 

with racks is shown in Figure 2.1, and example Region I and Region II rack configurations taken from 

Reference 9 are illustrated in Figure 2.2 and Figure 2.3, respectively. The focus of this evaluation is 

based on the application of BADGER to Region I and Region II spent fuel pool rack configurations. The 

different rack configurations are designed to account for different levels of fuel assembly reactivity and 

for more effective space utilization. Some variability exists within the rack designs themselves, including 

fabrication and material specifications in addition to design and dimensional differences. Materials 

susceptible to expansion or blistering, such as Carborundum or Boral®, can prevent fuel assemblies from 

being inserted or removed, as well as change the criticality control conditions. 
4 

Figure 2.1. Typical spent fuel pool for U.S. nuclear power plant (NRC file photo).
5 

Figure 2.2. Typical Region I spent fuel pool rack configuration. 

(Adapted from Reference 9 with permission of EPRI.) 

Figure 2.3. Typical Region II spent fuel pool 

(Adapted from Reference 9 with permis
6 

As an outcome of the observed in-service deterioration of Boraflex, the BADGER system was developed 

as a nondestructive in situ means to estimate the 10B areal density remaining in neutron absorber materials 

installed in spent fuel racks for the purpose of reactivity control. Examples of the material degradation 

experienced with Boraflex are illustrated in Figure 2.4 below, which indicate the potential for dimensional 

changes and compositional changes. The BADGER system would need to be able to detect these types of 

changes. A thorough discussion of the chemical and physical processes that result in Boraflex 

degradation is provided in Reference 10. 

Figure 2.4. Degraded Boraflex (from Reference 11 with permission of EPRI). 

BADGER employs a well-understood physics method of measuring the attenuation of thermal neutrons 

through an absorber panel between the neutron source and the detectors. American Society of Testing 

and Materials (ASTM) C1671 (Reference 12) discusses neutron attenuation, converting measured count 

rates to areal density through the use of calibration standards, and provides the following definition: 

neutron attenuation – for neutron absorber materials, a process in which a material is 

placed in a thermal neutron beam, and the number of neutrons transmitted through the 

material in a specified period of time is counted. The neutron count can be converted to 

areal density by performing the same test on a series of appropriate calibration standards 

and comparing the results. 

Although ASTM C1671 is specific to boron-based metallic absorbers for use in dry cask storage and 

transportation systems, it provides a discussion on the conduct of neutron attenuation testing for 

determining the 10B content of a neutron absorber material, which is similar in principle to what 

BADGER has been designed for and how it is being implemented. 
7 

The BADGER nondestructive test (NDT) device was developed in the mid 1990s and first reported in 

EPRI Topical Report TR-107335 (Reference 8). The system was designed to conduct scoping studies to 

evaluate the degradation (or loss) of 10B areal density in Boraflex in conjunction with the RACKLIFE 

(Reference 13) computational package. The RACKLIFE computer program was developed to assess inservice performance of Boraflex (Reference 14) and provide a predictive capability. Hence, it would not 

be considered applicable for use with other neutron absorber materials. The BADGER scan results have 

been used to establish estimates of neutron absorber panel 10B areal densities as well as to characterize 

dissolution and anomalies such as gaps and cracks. 

Several reports infer that BADGER testing has been conducted in a heuristic manner since its inception. 

These reports discus how process and design modifications have been implemented as operational 

experience has grown, challenges to system performance are encountered, and the range of applicability 

of the system is expanded. Some reports indicate that system refinements have been implemented 

including use of stronger sources, refinements to measurement processing software, and incorporation of 

computer models to help account for calibration cell and rack cell differences. Specific examples of 

inferences from Reference 8 include statements such as: (1) “...the experience at PB2 [Peach Bottom 

Unit 2] served to identify some changes to the test procedures and detector block which will improve the 

precision of the areal density measurements”; and (2) “Larger detectors have been added to the BWR 

BADGER systems based on the experience at MNS2 [McGuire Nuclear Station Unit 2]”. Other 

references such as Reference 15 (Part 3: NET-279-01) also support the conclusion regarding heuristic 

deployment, “Since different reference unirradiated panels from the previous test campaigns in 2000 and 

2004 were selected for the current campaign, an attempt was made to determine a conservative 

“correction factor” that can be applied to the relative % deviation (non-gap) to allow a comparison to 

previous campaign results.” 

Neutron detectors, signal-chain processing electronics, and data acquisition systems for conducting in situ 

measurements have advanced substantially since BADGER was first designed. Most of the 

advancements came after 2001, when an international effort began to test, evaluate, and ultimately 

improve the reliability and performance of radiation measurement systems. One of the more relevant 

advancements that is being used as a basis of the current state of the art regarding conduct of 

nondestructive assay (NDA) in this review was the development of ASTM Standard C1592M-09, 

“Standard Guide for Making Quality Nondestructive Assay Measurements” (Reference 16), which was 

first issued in 2004. 

The benefit of the last 15 years or so, with the increased requirements to implement performance testing 

radiation measurement systems for signal-to-noise effects, electromagnetic interference (EMI) 

susceptibility, radio frequency (RF) interference, and neutron/gamma (n/γ) discrimination, is that 

radiation measurement systems are more reliable than before. Radiation measurement systems not only 

require an extensive set of laboratory testing but also in situ test results to identify all sources of 

uncertainty, to take measures to identify all sources of bias and reduce these sources, and to ensure 

variance reduction techniques are employed to improve precision. A description of the BADGER system 

is provided in Reference 8, which was published in 1997. No other information was available for review 

describing the current status of the BADGER system or improvements that have been incorporated post 

2001 to indicate that the more recent advancements in technology and practice to improve nuclear 

measurement reliability and quality control (QC) have been incorporated. 

To facilitate a common terminology in the subsequent discussions in this report describing the materials 

used for calibration and test, the following additional definitions are provided. 

Calibration cell: portable arrangement of walls that contain neutron absorbers of known size and a 

certified/traceable 10B areal density. The calibration cell is used to calibrate BADGER over the range of 
8 

anticipated 10B areal density in the test panels. BADGER calibration is the process of fitting an 

exponential function of neutron transmission (ratio of the neutron count rates, attenuated to unattenuated 

region of calibration cell). The calibration cell configuration(s) are similar (but not identical) to BWR 

and PWR spent fuel pool rack cells. The calibration cell is transported between measurement sites. 

Standard panel: a neutron absorber panel in the calibration cell of known size and certified/traceable 10B 

areal density. 

Reference cell:an existing spent fuel pool rack cell that has a record maintained by the licensee of 

receiving no substantial gamma radiation dose, above which could alter the properties of the neutron 

absorber material. It is assumed that the neutron absorber panels associated with the reference cell are undegraded and unchanged from the as-built condition. The reference cell has also been referred to as the 

zero-dose panel or zero-dose cell. The purpose of the reference cell is to account for local, site-specific 

measurement variability in the design and manufacture of specific racks deployed in the spent fuel pool 

that are not accounted for in the calibration cell. 

Reference panel: a neutron absorber panel from the reference cell that is considered to be un-degraded, 

and from which all test-panel-measured neutron transmission measurement data is indexed against or 

referenced to. 

Test panel: a spent fuel pool storage rack panel within a rack cell that has been exposed to conditions that 

may degrade the 10B areal density. BADGER conducts neutron transmission measurements on a subset of 

test panels within the spent fuel pool storage racks, at nominally 72 vertical positions. 
9 

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10 

3 METHOD OF REVIEW 

Conducting a laboratory measurement of 10B areal density in a planar media can be quite easily 

accomplished with excellent repeatability (precision) and accuracy, with total measurement uncertainty 

(TMU) well below a few percent for a single-sided 95 percent confidence interval. However, challenges 

are encountered in the performance of these measurements within spent fuel pool storage racks e.g., 

operating under more than 6.5 meters (20 ft) of water, differences in rack designs, environmental 

instabilities affecting constant source-to-detector orientation, source/detector module wear over time, or 

background radiation. As a result, considerable uncertainties can be introduced when performing 

measurements under in-situ conditions. To implement the method effectively and to reduce uncertainty, 

controls need to be in place to ensure that proper engineering and/or administrative measures are taken. 

All measurements contain uncertainty. The magnitude of the uncertainty must be established to 

understand if the results are adequate for their intended purpose. According to the National Institute of 

Standards and Technology (NIST) Technical Note 1297, “Guidelines for Evaluating and Expressing the 

Uncertainty of NIST Measurement Results” (Reference 17), also known as the International Standards 

Organization (ISO) Guide to the Expression of Uncertainty in Measurement (GUM), components of 

uncertainty can be classified into different categories based on the method of evaluation: Type A and 

Type B. 

Type A uncertainty evaluation: 

An uncertainty evaluation based on any valid statistical method for treating data (e.g., 

calculating the standard deviation of the mean of a series of independent observations or 

using the method of least squares to fit a curve to data to estimate the parameters of the 

curve and their standard deviations). 

Type B uncertainty evaluation: 

An uncertainty evaluation based on scientific judgment using all relevant information 

available (e.g., previous measurement data, experience with or general knowledge of the 

behavior of similar measurements, manufacturer’s specifications). 

While a Type A uncertainty analysis is the principal objective of most uncertainty analyses, and preferred 

over a Type B analysis, there were no publicly available test records or peer-reviewed publications for 

BADGER showing how the BADGER system technical specifications have been satisfied. A Type A 

evaluation is “based on valid statistical methods for treating calibration and performance test data.” 

American Society of Testing and Materials (ASTM) test standards require a complete description of the 

test instrument, proper use of the instrument, interferences, sources of error, calibration, procedures and 

use, algorithms, precision and bias, and precautions. 

A variety of reports primarily from EPRI and Northeast Technology Corporation (NETCO) were 

reviewed for this assessment. In general, most of the NETCO documents for BADGER test campaigns 

were similar in format and provided post-processed results and limited numeric data that was insufficient 

to facilitate a detailed quantitative (Type A) uncertainty analysis. Recognition of this limitation is also 

reflected in Reference 10 (p. 5-24), where it is stated that “there is insufficient data to make confident 

calculations of uncertainties due to the calibration cell, but the following is observed....” Hence, only a 

Type B uncertainty analysis can be conducted on BADGER at this time. 
11 

This Page Intentionally Left Blank 
12 

4 BADGER SYSTEM DESCRIPTION 

Two BADGER systems have been fabricated, one for PWR spent fuel racks and one for BWR spent fuel 

racks. Initial design and fabrication testing was conducted in a clean pool at Pennsylvania State 

University, with spent fuel pool demonstration projects conducted at Peach Bottom Unit 2 and McGuire 

Unit 2, for the BWR and PWR systems, respectively (Reference 8). 

BADGER consists of four subassemblies: (1) a source and detector module, which is inserted into the 

spent fuel pool, with the neutron absorber test panel interposed between each module; (2) an 

electromechanical drive system to lower and raise the source/detector module; (3) nuclear electronics 

modules for each neutron detector; and (4) a data acquisition computer. An axial cross-section depiction 

of the BADGER systems is provided in Figure 4.1. 

Illustration recreated from Reference 8. 

Figure 4.1. Axial cross-section depiction of BADGER in operation in a spent fuel pool. 

(Adapted from Reference 8 with permission of EPRI.)

Pool wall Pool wall

Nuclear electronics Motor drive system

Overhead crane hook

BADGER source and 

detector heads

Spent fuel storage rack

Computer

Water
13 

4.1 SOURCE/DETECTOR MODULES 

For the BWR system, the heads consist of water-filled aluminum boxes, 5.75 in. (14.6 cm) per side with 

tapered lead-ins on the bottom surface, connected to aluminum suspension poles. The source head 

contains a watertight aluminum tube, which houses the 252Cf spontaneously fissioning neutron source 

when the equipment is in use. The detector head contains an aluminum block mounted on one inside face 

of the head, which houses four micro boron trifluoride (BF3) detectors. The detectors are encapsulated in 

watertight enclosures, which are sealed to the waterproof detector cables (Reference 8, p. 17). 

For the PWR system, the heads are similar, with major differences being in materials of construction and 

dimensions of various components owing to the larger rack cells for PWR assemblies (e.g., 8 in. 

(20.3 cm) per side with 6 in. (15.2 cm) height and tapered lead-ins). In the PWR system, steel suspension 

poles are used instead of aluminum, and the PWR source head is filled with high-density polyethylene, 

which contains a watertight aluminum source tube (Reference 8, p. 17). 

A cross-sectional view of the BWR BADGER system in optimum orientation within a representative 

spent fuel rack is presented in Figure 4.2. This simple illustration shows the neutron absorber between 

the adjacent cells, the neutron source head, and the four-detector assembly. 

Figure 4.2. Figure showing close proximity of source to absorber material and neutron 

detectors (BWR BADGER system). 

neutron source 

Source probe Detector probe

Al housing

neutron absorber panels

BF3 detectors 

pool water

steel rack cells

Al support block 

neutron shield

neutron absorber test panel 
14 

4.2 DRIVE SYSTEM 

An electromechanical drive system allows the source/detector heads to be lowered into the cells adjacent 

to the test panel of interest, and then moves the source and detectors axially up the test panel in 2-in. 

(5 cm) increments. The drive system consists of a stepper motor, gearbox, and winch assembly. A shaft 

encoder provides a precise measure of the vertical positioning of the source/detector module within the 

cell. A load sensor trips the drive motor if the source/detector head becomes stuck or lodged (Reference 

18). 

4.3 NUCLEAR ELECTRONICS 

Each of four neutron detectors is configured with independent signal chains. According to NETCO 

Drawing No. 092-01 (Reference 8, Figure 2-9), each detector is connected to a Tennelec Corporation 

(TC)-174 pre-amplifier. The coaxial cable length from the detector to the TC-174 is 40 ft (RG 59 or 

RG 62). The charge pulse from the TC-174 is fed to a TC-146 linear amplifier single-channel analyzer 

(SCA). A transistor-transistor logic (TTL) pulse out from the TC-246 amplifier is fed to a PC-based 

scaler board, the CTM-10 offered by Keithley Instruments. A mini nuclear instrumentation module 

(NIM) bin provides ±24 V ± 12 V power to the neutron detector high-voltage bias supplies (a TC-948) 

(Reference 8, NETCO Drawing 092-01, 8/14/1997). 

4.4 DATA ACQUISITION AND CONTROL COMPUTER 

The Keithley CTM-10 counter board/scaler is interfaced in the computer docking station to the analog 

data bus for controlling the source/detector head position. The computer interfaces via RS-232/485 serial 

communications with the stepper motor, shaft encoder, and load cell, all of which are used to position and 

control the source/detector heads. 
15 

5 BADGER SYSTEM DISCUSSION AND RELEVANT 

OBSERVATIONS ON UNCERTAINTY 

This section provides a description of factors that affect the measurement precision and accuracy of 

BADGER as implemented by the BADGER operator and data analyst. A Type B uncertainty analysis 

(Reference 17) of the BADGER system was performed with the recognition and understanding that 

available information for review was limited. An evaluation of the magnitude of uncertainties is 

presented, but it is incomplete from a quantitative standpoint because of a lack of published performance 

data on the calibration functions, background subtraction methods, establishment of the unattenuated zero 

intercept, data reduction methods, and conduct of Analysis Of Variance (ANOVA) tests on the influence 

factors affecting system precision and accuracy. The semi-quantitative estimate of uncertainties is 

developed based on best practices in the science of radiation-measurement-based nondestructive testing 

(NDT), national consensus standards, and an analysis of published BADGER results. 

The output of BADGER is the measured thermal neutron response from four separate BF3 detectors. 

From the neutron count rate, neutron attenuation ratios are developed from which absorber panel 

characteristics are derived such as absorber areal density, absorber gap locations, and distribution of gaps. 

Measured values may vary randomly from measurement to measurement as the result of several factors, 

including environmental fluctuations, operator inconsistencies, and inaccuracies in the vertical indexer. 

Some of these factors are intrinsic to the selected components and are correlated, while others are 

independent. A proper understanding of the measurement equipment, the principles of the test, and the 

influence of the environment is necessary to appropriately combine the individual component 

uncertainties into a TMU. Hence, combining the error terms in a meaningfully scientific fashion as in a 

complete Type A analysis is not possible. 

Customarily, in NDA/NDT systems if the device is to be used qualitatively (or for “indication only”), 

then a complete system design, reliability, and test package may not be required, depending on the 

application. However, as discussed in Reference 19, quantitative radiation measurement devices are 

typically designed with a clear set of specifications, operating conditions for deployment, interference 

factors that are understood and controlled in the implementation, administrative control points, and 

ultimately, acceptable tolerances/uncertainties over the range of performance. When the systematic 

uncertainties have been developed, boundary conditions can be set on the performance of each parameter 

with a corresponding “uncertainty budget” (Reference 17). 

A large majority of the measurement influence parameters that were evaluated as part of this study would 

have ordinarily been examined during a product design, development, and quality certification process. 

In this process, system technical specifications are written and qualified. BADGER product development, 

technical specifications, and experimental test reports were not available for review, therefore limiting the 

depth of this evaluation. Engineering design is typically used to improve the overall performance of a 

system in an effort to satisfy specifications that are established by the user of the measurement results. 

Engineering controls are developed to reduce measurement bias. Administrative controls are developed 

to reduce error—both systematic and random—during implementation on-site. In this context, quality 

control is a process used to ensure that measurement systems are performing to the requisite 

specifications within established and accepted component uncertainty ranges, and to identify when the 

process is out of statistical control and action is required to correct the problem. This is not to be 

confused with procedural protocols designed to reduce measurement uncertainty. 
16 

The following good practices for performing measurements are described in ASTM Standard C1592M-09 

(Reference 16). 

1. Identify all contributors to systematic error (bias) in the measurement. 

2. Eliminate all systematic error introduced in the acquisition of raw data. 

3. Evaluate remaining bias factors and either develop software algorithm correction factors to 

compensate for these factors, or propagate the effects of these factors into the overall uncertainty 

model equations through ANOVA or other suitable tests. 

4. Develop procedures that include steps to ensure that all engineering design features are 

implemented in the course of a measurement campaign. These engineering controls are necessary 

to ensure that the assumptions used in the uncertainty analysis are in fact valid. 

5. Calculate total propagated uncertainty in the calibration function that relates neutron transmission 

to 10B areal density and gap detection (width and length of gap). 

6. Develop administrative procedures to conduct QC tests of the instrument hardware to ensure 

hardware and data acquisition modules are within statistical control. 

When achieved, the TMU is estimated according to a mathematical construct like that offered by 

Reference 20: “A system bias represents a systematic error introduced into all measurements. If, during 

TMU development it is determined that a system bias is present, it is expected that a correction factor will 

be added to the software to remove the bias. In the absence of a system bias, the square of the Relative 

Standard Deviation (RSD)-measured, is equal to the sum in quadrature of the RSDs of item specific error, 

calibration error, and random error: 

RSD2

(Measured) = RSD2(item bias) + RSD2(calibration) + RSD2(random)” 

5.1 NEUTRON SOURCE 

5.1.1 Count Rate 

In neutron attenuation testing, the random, Poisson-distributed statistical relative error in neutron 

counting is equal to the square root of the number of counts divided by the number of counts (Reference 

12), assuming there is zero neutron background and no interference terms from neutron scatter. Neutron 

source intensity, measurement count time, and neutron detector efficiency are interrelated system design 

components to be optimized for performance, reliability, precision, and accuracy. For example, to 

achieve Poisson counting statistics of 1 percent, the total number of neutron counts per measurement 

point would be at least 10,000 per detector. With a reported 1,000 counts per detector, the relative 

theoretical Poisson counting error is 3.2 percent. Several plots show BADGER count rates in the 

absorber region less than 20 cps (e.g., Reference 8, Figures 3-16 and 4-10). Over a 10-second count time, 

this would result in a counting uncertainty no better than 7–8 percent. A low Poisson count rate and low 

detector efficiency may synergistically magnify the contribution to uncertainty from other factors, for 

example, not adjusting the discriminator to account for pulse pileup from high gamma-ray dose rates; 

differential loss (or gain) in neutron count rate from absorption, reflection, and moderation between 

source and detector; energy-dependent neutron flux down scattered below effective irradiation of the 

panel; and inadequate correction for 252Cf source decay. To reduce uncertainty, all detection 
17 

specifications should be proven sufficient to meet technical basis design objectives for a given source 

strength. No experimental data was provided to estimate the impact of “net neutron count rate from direct 

neutron absorption” on implementation of BADGER. 

5.1.2 Source Strength and Decay 

Short count time is a desired performance characteristic of the BADGER system for each axial elevation 

scan. A larger 252Cf neutron source strength may result in shorter counting times to produce a given and 

constant statistical error. To reduce the Poisson count error, count time may be extended or a higher 

intensity 252Cf source may be selected (Reference 21). With a yield of 2.34 × 106

 neutrons/second per 

microgram, safe handling limits of special-form 252Cf sources normally limit the useful mass to less than a 

milligram, or roughly a half a curie (1 Ci = 1.86 mg 252Cf). The 49 CFR §173.435 (Reference 22) A1 

quantity for 252Cf (domestic use) is 2.7 Ci or about 5 mg. This would be the upper limit for use by the 

system. It is important to decay-correct the source, given the relatively short half-life of 2.65 years 

(Reference 23), for all QC checks. If an aged source is used, then it is important to decay-correct using a 

method similar to that described by Reference 21. Typically, for measurement systems that use 

radioactive sources, as the selected source decays the minimum source intensity for ensuring that 

adequate counting statistics are acquired in the measurement time interval of interest can be identified in 

the system QC charts. 

The 252Cf source intensity can change by approximately 0.7 percent per 10 days of BADGER testing, 

resulting in a gradually increasing error on the measured count rate during a single BADGER 

measurement campaign. No experimental data was provided to estimate impact of source strength and 

decay on implementation of BADGER. 

5.1.3 Neutron Moderation by Covers on Heads 

An important physical effect associated with the selection and use of the 252Cf transmission source is 

related to the design of the source head assembly. Specifically, the neutron spectrum hardness (and 

intensity) should be matched for the local measurement conditions to reduce uncertainty considering 

(1) distance from the source to the neutron-absorber test panel wall, (2) design of neutron 

howitzer/collimator to obtain uniform neutron flux at the panel and of the optimum hardness, (3) local 10B 

density-thickness range of the neutron absorber, and (4) neutron moderator thickness for the detector head 

assembly. If the neutron transmission spectrum is too soft for the 10B density thickness of interest, the 

differential count rate per unit loss of absorber will be too small to be effective. These effects can lead to 

relatively large uncertainties in the calibration model selected for the test panels between the various 

measurement geometries for BWRs and PWRs, but most notably for the Region I flux trap design, where 

the transmission neutrons must travel multiple mean free paths before contacting the face of the test panel 

under inspection. 

No information was available for review on how these effects and issues are accounted for with the 

BADGER system to develop an uncertainty estimate. If not well evaluated and accounted for, the 

exponential slowing down of neutrons and absorption loss in any material other than the absorber under 

evaluation can lead to significant biases. 

5.2 DETECTOR CHARACTERISTICS 

No information was available on the make and model of the BF3 detector tubes used by the BADGER 

system. Parameters specific to the BF3 detectors, such as size, intrinsic efficiency, fill pressure, 10B 

enrichment, and materials of construction (i.e., wall materials and anode size and materials) all affect 
18 

detector performance. The uncertainties associated with these parameters are not independent and can 

vary depending upon external environmental effects (i.e., temperature). Trade-offs between these 

parameters are used within the design selection process to ensure that the target performance requirements 

are achieved. No information was available regarding performance requirements for the detectors used 

by BADGER. An example performance requirement is “the usable thermal neutron sensitivity in a 

gamma field of 103

 R/hr shall be equal to or greater than 5 counts per (second·nv) with the system 

adjusted to permit no more than 1 count per second background caused by gamma-induced pulse pileup” 

(Reference 24) (nv is the product of neutron density, n, in neutrons per cubic centimeter, and velocity, v, 

in centimeters per second). Another characteristic of importance, particularly for multi-detector systems, 

is detector-to-detector manufacturing tolerance. For multiple BF3 tubes operated with one high voltage 

power supply, gain-matching of the tubes must be accounted for in not only evaluating efficiency changes 

(between detectors), but also for adjusting the lower-level discriminator (LLD) when gamma-ray 

interference becomes an issue. The performance characteristics are certified by the manufacturer and 

provide well-established uncertainty ranges associated with the design for a given operating environment 

range. In systems such as BADGER, these performance metrics are evaluated and controlled in 

accordance with QC charts to ensure that the desired level of performance is maintained within the known 

uncertainty range, or budget. As indicated in Reference 25, selecting a proper neutron detector for a 

specific application requires a combined engineering evaluation for establishing trade-offs in the 

interdependent design parameters, as described below. 

5.2.1 Size 

The BF3 detectors used by BADGER are either 1/2 in. (1.3 cm) or 5/8 in. (1.6 cm) in diameter for the 

BWR and PWR systems, respectively, and have a 2 in. (5 cm) active length (Refs. 8 and 18). Typically, 

during measurement system design such as the BADGER system, the designer evaluates trade-offs 

between uncertainties and optimizing detector operational aspects when developing the engineering 

specifications. Examples of trade-offs include using a longer or larger diameter tube, the effect of n/γ

discrimination, or broader spatial resolution. This specific technical information is either proprietary or 

not available. The effects of detector tube diameter are discussed further in Section 5.4.5. 

5.2.2 Efficiency 

Because the neutrons are in a scattering medium, taking the area of the detectors subtending the solid 

angle at a distance, r, from the source (ܣ/ሺ4ݎߨ^2 ሻ) is not applicable for characterizing detector 

efficiency. Detection efficiency is integrated over the energy-dependent macroscopic absorption cross 

section for the BF3 gas in the detector. Variation or bulk differences in the materials, material 

thicknesses, and moderator atom density between the source and detector significantly affect the 

integrated count of the detector. To quantify the uncertainty in efficiency, the efficiency can be tested 

empirically over the range of measurement geometries: Region I, Region II, or any BWR- or PWRspecific rack design, adequately accounting for the various magnitudes of the moderating region between 

the source and the detectors. This specific technical information is either proprietary or not available. A 

specification sheet for the neutron detector operating characteristics was not provided. 

5.2.3 Fill Gas Pressure 

The gas pressure can impact the magnitude of the individual pulses related to gamma-ray interactions in 

the counter walls and gas. Reference 26 indicates that BF3 is particularly sensitive to contamination in the 

fill gas, especially at high pressures. This is reaffirmed in Reference 27, where it is stated that the 

performance of BF3 as a proportional gas is poor when operated at high pressures, so typical tubes limit 
19 

the pressure to about 0.5 to 1.0 atm. No experimental data was provided to estimate the impact of fill gas 

pressure on BADGER system performance. 

5.2.4 10B Enrichment of the Gas 

Neutrons are detected in the boron trifluoride (BF3) gas based on the 10B(n, α)

7

Li reaction. To improve 

detection efficiency, the BF3 is typically enriched in 10B. Reference 27 indicates that commercial BF3

detectors are highly enriched in 10B, resulting in an efficiency of approximately five times greater than if 

the gas contained naturally occurring boron with a 10B to 11B natural abundance of 20 weight percent and 

80 weight percent, respectively. No information was available for review regarding the 10B enrichment in 

the BF3 tubes used by BADGER. However, most practical BF3 counters are filled with boron trifluoride 

enriched to approximately 96 percent 10B (Reference 27). The determination of 10B enrichment is made 

during the design specification test stage of the project and is not known. 

5.2.5 Aging of BF3 Detectors 

All instrumentation ages from a variety of environmental factors. The BF3 tubes used by BADGER are 

sealed counters, which can eventually develop leaks and gradual contamination of the fill gas. Quality 

control charts are typically established to detect out-of-tolerance detector and electronics performance. 

Reference 8 (Section 4.2.1) indicates that the detector becomes inoperable if water leaks into it. In the 

case of aging detectors, a QC chart maintained with a neutron check source will reveal when breakdown 

in the detector has occurred, or when detector degradation is sufficient to require replacement. An 

example QC check requirement could be that the count rate be maintained within ±5 percent of expected, 

per 100 hours of testing (Reference 24). Quality control procedures, methods, and QC results are not 

available for BADGER in order to make a determination on uncertainty contribution. 

5.2.6 Detector Wall Material 

Wall materials selected for the neutron detector can influence detector performance due to the interaction 

of gamma-rays in the detector wall. The physical process in selecting the wall material that contributes to 

uncertainties is n/γ discrimination (Reference 28, Section 13.3). This dependence is primarily based on 

the gamma-ray induced Compton electron production in the wall, which in turn produces a column of 

ionization as it traverses the detector. Pileup pulses caused from the ion pairs created in the detector 

from secondary gamma interaction becomes problematic in small BF3 detectors and needs to be properly 

engineered and tested in gamma-ray fields greater than several hundred rads per hour for use in spent fuel 

pools. Materials typically used for BF3 tubes consist of aluminum, copper, and steel, with aluminum 

having the lowest thermal neutron absorption cross section of the three materials. A detector model was 

not provided, and a specification for wall material was not available; therefore, no estimate of uncertainty 

can be provided on this important neutron detector property and operating characteristic. 

An additional uncertainty associated with the wall material that can affect the counting data can result 

from the BF3 detector tube manufacturing process. A study conducted in Reference 26 indicates that in 

low-neutron-density counting configurations, background count rates could be of the same order of 

magnitude as the expected neutron event counting rate. Background counts can be generated as a result 

of alpha surface contamination of the wall material. Results of the study found that background counts 

could vary considerably among the different counters tested, but counts were also found to be correlated 

with inside surface area when the counters were from the same manufacturer. Background count rate 

variability ranged from 0.005 to 0.05 counts per minute per square inch of inner surface. As discussed in 

Section 5.6, there is no information available regarding how the background count evaluation is 

performed. 
20 

5.3 INTERFERENCE 

5.3.1 Background Neutron Flux from Surrounding Assemblies 

The BADGER operator’s preference for a panel scan, provided the spent fuel pool has the flexibility for 

fuel movements, is to remove all neutron sources, e.g., spent fuel assemblies, from the cells surrounding 

the test panel. In order to minimize neutron streaming into the detectors from neutron sources other than 

the 252Cf-attenuated neutron beam, a minimum of at least two, and preferably three, cells surrounding the 

test panel should be clear of spent fuel assemblies.* The detector block is also equipped with a neutron 

shield on the back and sides as a mitigation measure against neutrons streaming into the detectors from 

other sources. However, because the number of cleared cells proximate to the test panel is unknown, and 

appears to vary during actual deployment of BADGER, there is a possibility of fast neutrons streaming 

through the adjacent cells without being absorbed and reaching the detector in the epithermal range 

sufficient to lead to a small number of counts. 

No experimental data is available on the design of the detector cavity to shield the sides, top, bottom, and 

back from in-scattered neutrons (neutrons other than from direct transmission); however, there was some 

discussion of scatter effects based on MCNP modeling of the system in Reference 29. Uncertainties due 

to background flux could be reduced if the neutron shield was selected and designed for maximum 

effectiveness, and confirmed by laboratory experiments. In-scattered flux can be determined by removing 

neutron absorber panels from around the detector head, one at a time, and measuring the total neutron 

flux. For each panel removed—top, bottom, rear—the count rate in the detectors should increase from 

the in-scattered flux. From the reports publicly available, there is no scientific means to estimate, as 

implemented, the degree of bias from neutron in-scatter, reflection, and absorption from adjacent 

materials in the rack. 

5.3.2 Gamma Interference 

Gamma-ray interaction probabilities in the wall and in the gas of the detector tube are relatively small, but 

when gamma-rays interact in the wall or BF3 gas, secondary electrons are created, which, in a 

proportional counter are swept to the anode, creating small-amplitude pulses – “noise.” A more detailed 

description of how gas-filled detectors detect radiation is available in Reference 30. As the gamma-ray 

flux increases, an electron shower is created in the detector tube. The small pulses from the electron 

shower are integrated over the time constant of the tube, creating a charge pulse that is proportional to the 

total charge collected. In a BF3 proportional counter, the neutron reaction products from the 10B reactions 

produce much larger pulses than the electrons produced by the photons. However, as the gamma-ray flux 

increases the pulse amplitude from the gamma-induced electron shower increases, to an extent that the 

pulse height may be equal to or greater than the amplitude affiliated with the collection of charge from 

neutron interactions. Above this energy-dependent gamma-ray dose-rate threshold, a pulse from gammaray interactions cannot be discriminated from a neutron detection event. Different wall materials and 

thicknesses will result in different reaction rates. By using a discriminator, i.e., the SCA, as discussed in 

more detail in Section 5.4.5, the counter can be set to read only the larger pulses. 

If the design of the detectors and electronics has not been selected and evaluated properly, neutron count 

results will be erratic and unreliable. Because of the high radiation environment near spent fuel activated 

hardware in the spent fuel pool and the small detector tube diameters, gamma-ray interference is an 

important aspect that needs to be controlled. Without proper n/γ discrimination the detector will count 

 

*. Personal communication with Thomas C. Haley, 2012. 
21 

gamma-rays as neutrons, and in a high gamma field above the detector design limit, the detector may 

saturate and essentially fail, e.g., register very high number of counts. An example of process controls 

outside the operation limits is provided in Reference 15 (Part 3: NET-229-01), where during the testing 

process, one of the BF3 detectors was identified as becoming sporadically operative due to suspected 

gamma radiation damage from a spent burnable poison assembly in a cell adjacent to cells being tested. 

The uncontrolled environment was due to operator error and using the system outside its range of 

applicability. If the detectors are used outside the range of applicability, the measured result can be 

significantly in error. In this example, the detector actually failed, and the results from it were no longer 

used. However, all detector results from that test campaign could be significantly in error if they were 

operated outside the rated detector specification limits. 

During design, the instrument specifications for n/γ discrimination are determined based on the 

anticipated neutron count rates and photon exposure rates to be encountered (this is further discussed in 

Section 5.4.5). Hence, the detector uncertainty should essentially be low (<2 percent on count rate) or 

within manufacturer specifications when operated in accordance with the design limits. If operated 

outside the design limits, then the counting results are unreliable. This parameter must be thoroughly 

evaluated in the design-specification period of system development. Failure to discriminate gammainduced signals could be the most significant contributor to uncertainty, if uncorrected. Provided the 

neutron detector and electronics are specified and tested properly (to account for the high radiation dose), 

then a QC program can be put in place to manage detector uncertainty due to gamma interference. If the 

gamma-ray flux is too high, then a different detector with a higher Q-value, such as a fission chamber, 

could be employed. 

5.4 ELECTRONICS 

The nuclear electronics used by the BADGER system include a preamplifier, amplifier, discriminator/ 

single-channel analyzer (SCA), high-voltage power supply, and data acquisition board/scaler. A basic 

circuit diagram for a BF3 counter is illustrated in Figure 5.1. 

Figure 5.1. BF3 circuit diagram. (Source: Reference 30.) 

Similar to the design selection of the detectors, the uncertainties associated with selection of the 

electronics components are not independent and can vary depending upon external environmental effects 

(e.g., high gamma-ray field). During the design process, trade-offs among these parameters are evaluated 

in order to select a design which ensures that the target performance requirements are achieved. The 

performance characteristics of the electronics modules must be certified for use with established 

uncertainty ranges. These components are controlled in accordance with QC charts to ensure that the 

desired level of performance is maintained within the known uncertainty range. No specific performance 
22 

requirements were available for the parameters described in the following subsections to support an 

estimate of associated uncertainty contribution. Typically, with regard to nuclear electronics, it is not an 

uncertainty but an erroneous result that occurs when the components are not selected properly. 

5.4.1 EMI Susceptibility 

Electromagnetic interference (EMI) can be a significant problem in nuclear detectors and electronics. 

Interference manifests itself as spurious counts in the signal train. All nuclear measurement instruments 

need to be tested to ensure that the interferences from EMI are corrected for, or minimized, in the design 

phase of the project. The test requirements for this parameter are provided in International 

Electrotechnical Commission (IEC) Standard 61000-4-3, “Electromagnetic compatibility (EMC) – 

Part 4-3: Testing and measurement techniques–Radiated, radio-frequency, electromagnetic field 

immunity test” (Reference 31). Additional guidance and explanation of the physical problem is provided 

in NUREG/CR-5609, “Electromagnetic Compatibility Testing for Conducted Susceptibility Along 

Interconnecting Signal Lines” (Reference 32). 

It is not known whether BADGER is Underwriters Laboratories (UL) listed or CE marked. It is also not 

known what degree or level of environmental testing was performed on the system to meet the intention 

of the IEC standards. 

5.4.2 RF Pickup 

The degree to which RF interference and susceptibility affect the BADGER system could be quantified 

according to the IEC standards presented above in Section 5.4.1. 

5.4.3 Amplifiers, Discriminators, Power Supply, Acquisition Board 

Field problems such as spiking in neutron count rate, noise in signal processing chain from RF pickup, or 

EMI susceptibility have been reported (Reference 10), suggesting that instrument error and uncertainty 

can be significantly greater than anticipated, especially when quantitative results are desired. A large 

majority of this error may simply be due to using 15-year-old NIM bins and analog nuclear electronics, 

which age with time. Additionally, the BADGER electronics diagram (Ref. 8, Figure 2-9) indicates that 

the preamplifier is located about 40 ft from the detector tube. Typically, the preamplifier is located as 

close to the detector as possible to minimize noise or signal degradation from the length of the cable. 

Uncertainties may be reduced if signal chain processing is improved, particularly given the recent 

improvements in both analog and digital electronics for counting neutrons. 

5.4.4 Signal Processors 

The signal processing electronics such as preamplifier, amplifier, scaler, and acquisition board need to be 

selected based on environmental specifications required of the measurement. If the signal processing has 

not been proven to be reliable (i.e., with regard to noise; RF pickup; EMI susceptibility; cabling 

connection issues; impedance-matched cables, preamp, amp; etc.), then the system is not reliable. 

Applicable Institute of Electrical and Electronics Engineers (IEEE), ASTM, IEC, ISO, and American 

National Standards Institute (ANSI) standards are available to assist in the overall design and 

procurement effort for system components. 
23 

5.4.5 Discriminators for Pileup Rejection, Wall Effect 

Neutrons are detected in BF3 proportional detectors via the 10B(n,α)

7

Li reaction. The 10B neutron 

absorption reaction results in the production of an alpha particle and a 7

Li recoil nucleus that travel in 

opposite directions. When the kinetic energy from these particles is completely deposited in the detector 

fill gas, a large pulse is recorded with a typical reaction energy (Q-value) of 2.31 MeV (94%) or 

2.79 MeV (6%) (Reference 27). Because the tube diameter is small relative to the range of both the alpha 

particle and the 7

Li ion, a significant fraction of neutron-induced charge pulses, the alpha particle and 

recoil lithium ion nucleus, strike the wall before depositing all of their energy in the fill gas resulting in a 

significant fraction of charge pulses of smaller amplitude than a “full energy” event, ranging from ~0.84 

MeV and higher. The cumulative effect of the particle interactions with the wall is known as the “wall 

effect” in gas chambers and results in incomplete charge collection at the anode. The wall effect is not 

significant in neutron counting when gamma-ray fluence rates are small, for example, less than 10 mR/h. 

With higher gamma-ray fluxes, the wall effect combined with the gamma-ray interference becomes a 

significant issue: gamma-ray interactions are counted as neutrons, as described further below. To offset 

the gamma-ray interference effect, the lower-level discriminator is set to reject gamma-induced pulses. 

The wall effect becomes more pronounced as the detector tube diameter is decreased. A small fraction of 

neutron interactions, depending on angle of incidence and location of interaction within the tube can 

result in both recoil nuclei striking the wall. This is seen as a slightly lower-energy tail to the left of the 

0.84 MeV pulse. 

As the gamma-radiation field intensity increases, the number of photon interactions in the gas and 

detector wall increases. In other words, a high number of gamma rays produce a high number of 

secondary electrons that can add up to a high enough amount of energy to register as a false neutron 

count. All pulses above the LLD and below the upper-level discriminator (ULD) are recorded as neutron 

count events, which represents the detector system count window that would be set on a SCA. If the LLD 

is set too low for the environment being measured, then gamma-ray induced pulses would be counted as 

neutrons. The LLD must be set to a higher energy than these pileup pulses to avoid spurious counts in the 

neutron pulse window. However, as the LLD setting is increased to reduce the impact of pileup pulses, 

the counts per unit neutron flux are decreased. A smaller fraction of the true neutron signal is integrated 

over the pulse height distribution. Hence, neutron detection efficiency is reduced. The effect on 

efficiency for a given count window size can be accounted for during calibration, but the effect on the 

neutron count rate above the LLD from gamma-rays is highly-variable and not something that can be 

estimated through calibration. 

5.4.6 Dead Time 

The BADGER system operates in “pulse mode,” where the signal from each interaction is processed 

individually. One of the main problems with detection systems that operate in pulse mode is that two 

interactions must be separated by a finite amount of time if they are to produce distinct signals. This time 

interval is referred to as the dead time of the system. Interactions that occur during the dead time are not 

counted resulting in lower count rates. Dead time losses can become problematic when high counting 

rates are encountered. No technical information was provided to evaluate the effect of dead time. 

5.5 APPARATUS GEOMETRY 

A number of design and fabrication parameters are reflected in the conduct of making an accurate neutron 

transmission measurement. It is much simpler to control the measurement when performed on coupon 

samples removed from the spent fuel pool. In coupon interrogation, the measurement geometry—

between the source-coupon detectors—can be very accurately controlled using precision counting jigs and 
24 

counting assemblies. ASTM C1671-07 describes the qualification and acceptance process for neutron 

absorbers, including a goodness-of-fit test for determining a confidence interval based on coupon 

sampling. In addition, a new ASTM standard committee has been formed to write a standard for 

laboratory-grade coupon neutron transmission measurements. As a general rule, the accuracy and 

precision of any NDA/NDT device employed in situ is typically two to three times worse than for 

laboratory sample/coupon analysis. That is to say, suppose a laboratory measurement can be made with a 

TMU of ±5 percent; designers of a comparable in situ method will be challenged by in situ geometries 

and environmental conditions such that making a measurement with a TMU of “just” ±10 percent to ±15 

percent becomes a substantial design goal. For the overall BADGER instrument, it should be stressed 

that the apparatus geometry for neutron transmission measurements in situ is the most substantial 

contributor to error (assuming a good calibration and that n/γ discrimination is acceptable), and in this 

case specifically because the 252Cf source irradiation is a broad, conical beam across the face of a panel, 

and the measurement geometry is a near-field measurement such that any variation in the source-to-panel 

and panel-to-detector geometry will cause a significant change in neutron count rate. 

In the case of BADGER, which is an in situ NDT method, it is exceedingly difficult to design, fabricate, 

and thereby control the important measurement parameters governing neutron moderation, reflection, and 

absorption consistently within a panel, and between panels. A broad beam, conical neutron transmission 

measurement across a surface, in situ, is by nature difficult to perform with any type of laboratory-grade 

precision and accuracy. Many factors come into play because of the neutron slowing-down process and 

ultimately the reliable and consistent detection of neutrons in a confined and less than ideally 

characterized measurement geometry. This was discussed in the MCNP modeling effort (Reference 29). 

Specific parameters of influence that can affect measurement performance associated with the apparatus 

geometry are (1) head misalignment, (2) rack cell fit, (3) use of mechanical controls, (4) rack cell 

variations and deformations, and (5) use of detector data to represent panel coverage. 

5.5.1 Head Misalignment 

Source and detector head misalignment can have a significant impact on measurement results. The term 

"misalignment" refers to any orientation where the source and detector heads are not flush with the cell 

wall between them. The relative error is magnified at close measurement geometries (e.g., a few inches) 

among the source to absorber panel, and absorber panel to detector probes, such that any distortion in 

counting geometry will affect the neutron flux in the detectors, considerably. The optimum counting 

geometry and three misalignment variations possible in counting geometry – tilt, twist, and offset – were 

adapted from Reference 8 and are shown in Figure 5.2. The effect of geometric measurement error is 

exponential: the neutron count rate in any given neutron detector varies exponentially with placement. 
25 

Figure 5.2. Detector probe orientation. (Adapted from Reference 8 with permission of EPRI.) 

At such close range, a minor 1⁄4-in. (0.6 cm) shift in the neutron detector away from the source can result 

in a count rate change of approximately 10 percent. The bias on areal density is approximately the product 

of the bias in count rate and the slope of the calibration curve, resulting in a 10B areal density change by at 

least 20 percent. While the front-to-back geometric variation is the most extreme case, side-to-side 

geometric variation and detector-source twisting can also introduce large uncertainties. Relative average 

areal density uncertainties of 15 percent to 43 percent were observed in the SCALE models represented in 

Appendix A. In addition to the geometry change, misalignment uncertainties are also dependent upon the 

panel areal density being scanned. These results are illustrative uncertainties based on a BWR Region II 

rack module design. The relative uncertainty is expected to be similar in magnitude for other unborated 

Region II rack modules but would be expected to be higher for borated moderator systems and flux trap 

rack designs as a result of the overall reduction in thermal neutron count rates. Uncertainties in BADGER 

as deployed may be more accurate if they are evaluated by direct performance testing of the device, for 

example by destructive examination of test panels, rather than by estimating with Monte Carlo neutron 

transport calculations, as performed in this report and as discussed in Reference 29. 

a.) Tilt

b.) Twist

c.) Offset

Optimum Misalignment
26 

5.5.2 Rack Cell Fit 

Uncertainty associated with the rack cell fit can result in head misalignment as discussed in Section 5.5.1. 

Section 5.5.3 discusses the use of mechanical controls to reduce the potential for misalignment. Any 

other uncertainty introduced from rack cell fit issues will be site and/or rack module specific and will vary 

from pool to pool. Therefore, no general estimate of uncertainty can be provided at this time. 

5.5.3 Compression Springs, Shims, Vertical Offsets 

As discussed in Section 5.5.1, tilt, twist, and offset geometry variations can have a significant impact on 

the reported areal densities as determined with the BADGER system. Even though two BADGER 

designs have been constructed, one for PWR assembly racks and one for BWR assembly racks, to account 

for the rack cell size difference, variability still exists among rack designs. When the clearance between 

the rack cell walls and the detector heads is large, shims are used to mechanically reduce the range of 

lateral movements. In addition, a compression spring has been mounted above the heads to keep each 

module butted flush against the rack cell wall under investigation, and to ensure that the source-paneldetector assemblies are held firm against each other, and constant along the length of a test panel to the 

fullest extent practicable. The desired level of compression by the spring being applied unevenly, or shim 

wear, could introduce a bias due to head misalignment. 

Vertical offset is a difficult geometric effect to control. With a 2-inch (5 cm) BF3 detector, any small 

change (e.g., fraction of an inch) in the vertical offset will create a relatively significant change in neutron 

count rate similar to that discussed in Section 5.5.1.To maintain low uncertainty due to head offsets, 

routine checks and inspections can be conducted to ensure that mechanical controls are performing as 

desired. 

5.5.4 Effect of Rack Cell Deformation: Panel Cladding Bulges, Collisions 

with Assemblies 

References 9 and 33 identify some physical characteristics that are expected to be encountered during 

BADGER measurement campaigns: Boraflex shrinks, cracks, and develops gaps; Boral® blisters and 

bulges; Carborundum warps, stretches, and shrinks; and spent fuel racks can warp over time. As a result, 

maintaining well-characterized counting geometry can be challenging, depending on the magnitude of 

these physical deformities in the panels. The contribution to measurement uncertainty from physical 

effects in the deformation of the test rack cell may be mitigated if the calibration cell incorporates a set of 

calibration plates exhibiting similar effects. The bias in this term must be evaluated since the relative 

change in the counting geometry is significant due to (1) broad beam irradiation of point 252Cf source 

across panel surface ~3–4 in. (7.6 – 10.2 cm) from source; (2) detectors ~0.5 in. (1.3 cm) from panel; and 

(3) bulges reported with dimensions of 1⁄4 in. (0.6 cm) or more. Neutron transmission measurements are 

very sensitive to these changes in measurement geometry. Uncertainty in areal density values would be 

similar to or greater than that described in Section 5.5.1 across an axial segment where deformation 

exists. 

5.5.5 Determination of Detector Coverage of Panel Area 

A broad-beam point source projection across a panel surface several inches from the source is subject to 

specific measurement controls that need to be in place to ensure the uniformity of the irradiation. 

Uncertainty can be quite high, as opposed to a uniform, "pencil-beam" irradiating flux used in a 

laboratory-grade coupon-sample analysis (ex situ). According to Reference 8, the number of detectors 

selected (four) was based on the appearance of gaps of a specific size in the early 1990s, based in part on 
27 

coupon samples that had been analyzed as well as other in situ blackness testing measurements. It is 

difficult to read the raw trace data from the BADGER reports to determine whether detector coverage is 

complete or not; however, there are some adjustments that can be used in the data reduction algorithm to 

look at the effective growth of a gap along the horizontal plane. 

Provisions do not exist in the data reduction software to correlate the count rate in the two outer detectors 

relative to the two inner detectors. This is left up to the operator (or analyst) to examine this ratio and to 

identify nonuniformity of 10B areal density across the panel width laterally. This is a subjective 

evaluation, and not always performed, that in turn is used to reexamine or reestimate the integrity of the 

neutron absorber at the edge (edge dissolution). A description of how the BADGER scan data is 

interpreted is provided in Section 5.2 of Reference10. Each of the four neutron detectors has its own 

specific calibration curve, and averages between the inner and outer detectors can be compared for 

consistency across an axial segment of the panel. 

5.6 CALIBRATION 

Although not described in any of the BADGER reports, prior to the conduct of a measurement inspection, 

most measurement systems are tested to ensure that the electronics are performing within specification 

according to control charts that are kept for each system. Electronic adjustments may be made to ensure 

that the lower-level discriminator on the amplifier is set properly (for n/γ discrimination), that the highvoltage plateau is established on each of the four neutron detectors, and that the source-decay-corrected 

neutron rate in the detectors measured from the 252Cf is within nominal statistical expectation. In addition 

to the electronic tests of the nuclear instrumentation, the neutron background in the vicinity of the 

calibration panel and the test panels needs to be evaluated. There was no evidence in the open literature 

on how the background evaluation is performed. Good practices for calibration, as discussed in ASTM 

C1592M-09 (Reference 16), can lower uncertainty. Once the system is proved to be within statistical 

control, accurate calibration cell scans can be conducted. 

Calibration is the engineering process of relating the measurement system response (measurand) to the 

derived parameter of interest. A calibration curve relates the measured neutron count rate to 10B areal 

density and to percent degradation from the reference panel. The calibrations performed on-site are 

described to some degree in Reference 34, but several of the specific calibration and data reduction steps 

necessary to construct the mean square error (MSE) terms in the calibration matrix are not publicly 

available. Therefore, all calculations performed in this section use data for illustrative purposes only. 

This is a significant limitation of attempting to estimate uncertainty in the calibration functions alone. 

5.6.1 Number, Range, and Precision of 10B Areal Density of Standard Panels 

A calibration mathematical relationship (or function) is developed from a calibration cell consisting of a 

range of absorber plates with known 10B areal densities. Reference 10 indicates that the calibration cell 

contains Boraflex panels of various known 10B areal densities with well-characterized gaps. The 10B areal 

densities of the calibration panels were reported as known from material certification sheets and verified 

by chemical assay and neutron attenuation testing. 

Based on the information reviewed, it appears that the calibration cell has changed over time. A single 

rack cell configuration from 1998 is described in Reference 29 as being composed of a rack cell with a 

single region for absorber panel placement representative of a Region II rack on one side and a Region I 

rack on the other. Although not explicitly stated, it is assumed that absorber panels of different areal 

densities are placed axially in order to develop the calibration curve. A more recent description (i.e., 

2010 report) discusses a 3×3 calibration cell, illustrated in Reference 35 (Figure 2-4), that contains 21 
28 

different standards including four Boral® standards (Reference 35, Table 2-1), and a specific reference 

panel that is representative of panels in the Turkey Point 4 Region 2 racks. Consistent with the 

information presented in Reference10, processes described in Reference 12, and assuming that the 

development of the calibration cells and panel certification process would have been controlled under an 

NQA-1 quality assurance program (Reference 36), there would be objective evidence which demonstrates 

that potential uncertainties in the calibration due to 10B areal density uncertainty in the calibration 

standards are negligible. However, this type of information was unavailable for review; therefore, no 

estimate on uncertainty can be made. 

When fitting exponentially distributed measurement data, in particular, it is important to select the range 

of calibration plates over the range of use of the device, to determine and optimize the number of 

calibration plates around the test panel 10B areal density. Regarding the number of calibration standards, 

Reference 37 (Section 2.3.6.2) indicates that a minimum of five discrete known calibration plates of 

specified 10B areal density are required for a linear calibration curve, and that 10 plates should be 

adequate for more complicated models. It is noted in Reference 16 that the amount of effort expended on 

calibration should be commensurate with the quality objectives of the measurement results. Calibration 

standard and curve data were unavailable for review, so no estimate on uncertainty can be provided. 

5.6.2 Standard Panel Degradation 

A standard panel in this subsection is in reference to the different calibration standard panels that make up 

the calibration cell. As implied in Reference 8 and Reference 35, a calibration cell is brought from site to 

site and lowered into the pool at the beginning of the BADGER measurement campaign. After it is used 

to develop a calibration function, it could be removed immediately, or after the measurement campaign is 

completed. Either way, the time in pool, and therefore its exposure to gamma radiation, will be minimal, 

so the expectation is that there should be negligible degradation of the calibration standard panels. This 

can be confirmed with a proper QC program and establishment of an inspection process. Uncertainty 

associated with degradation of the calibration standards should be negligible in comparison to the other 

factors that can influence measurement error. 

However, if a calibration standard panel(s) suffers degradation, this will result in increased spread of 

transmission ratios about a given standard areal density and should be reflected as additional uncertainty 

associated with the calibration curve fit to the data points. Because the calibration cell is only used for 

determining the slope, this uncertainty would propagate forward as a slope uncertainty when the test panel 

areal densities are being calculated. The uncertainty in 10B areal density measurement of the test panels 

will be directly proportional to the increased uncertainty associated with the calibration standard panel 

degradation. 

5.6.3 Adjustment of Calibration Procedure for Specific Pool Characteristics 

BADGER conducts a relative, not an absolute, measurement. When the physical properties of the 

inspected panel and the calibration panel are identical, accurate relative measurements can be made. 

Ideally, the materials and the geometry of the rack would be identical to those of the calibration cell. 

Unfortunately, this is not the case because of differences in rack modules between various spent fuel 

pools. Some physio-geometric differences between calibration cells and rack cells may impact 

measurement uncertainty commensurate with the degree of difference, but may also invalidate the 

calibration function for the rack cells. Pool-specific characteristics contribute to uncertainty associated 

with the calibration process. Therefore, adjusting the calibration procedure to account for rack- and 

spent-fuel-pool-specific characteristics reduces uncertainty. For example, a difference in flux trap 

spacing (for different spent fuel pool racks) can cause a shift in the neutron energy spectrum from what 
29 

was used for establishing the slope in the calibration function. Additionally, adjustments to account for 

significant differences between rack cell configurations and the calibration cell configuration may be 

necessary. 

Some test reports such as Reference 18 list NETCO-developed pool specific procedures in the reference 

sections; however, the information was unavailable for review. 

5.6.4 Relevance of Standard Panel Material to Rack Panel Material 

The effects of self-shielding, streaming, and channeling of neutrons between absorber particles can vary 

significantly for different materials. Neutron channeling and streaming occur when the distribution of 

boron in the absorber panel matrix is heterogeneously distributed such that a path between boron particles 

exists that allows neutrons to penetrate the absorber sheet without attenuation. Self-shielding is in 

reference to the neutron absorber particles at the surface absorbing neutrons before they can penetrate 

deeper into the absorber material. The materials’ heterogeneity parameters (e.g., particle composition, 

size, dispersion) of the calibration cell and test panels must be similar for accurate calibration. The effect 

of heterogeneity of composition is more pronounced in soluble boron environments. For example, 

consider a PWR spent fuel pool that contains soluble boron in the moderator and test panels with different 

levels of degradation. The test panels that have exhibited degradation may have void regions within the 

panels with different porosity levels. In addition to water moderator, these pores could also contain 

soluble boron that would not be captured in scans of the calibration standards or the reference panel but 

will affect the thermal neutron attenuation rates. The impact of this difference in heterogeneous 

properties depends upon the amount of degradation, the areal density of the test panel, and the amount of 

soluble boron present in the pores. In addition, neutron in-scatter will be dependent on local measurement 

perturbations from scallops, warp, and geometric effects. 

To account for differences between the standard panel material and the rack panel material, including but 

not limited to: inhomogeneities, composition changes, material losses, and dimensional changes, 

approptiate adjustments or correction factors would be needed to ensure that the physical measurement 

distortions, compositional changes, and all other relevant differences are accounted for when developing 

calibration model uncertainties. Alternatively, if like-for-like characteristics are not available, 

computational assessments and bounding system performance studies could possibly be conducted to 

estimate TMU introduced by the physical differences between the calibration panel, reference panel, and 

actual panel under test. These assessments and studies would need to account for physical differences 

between the standard panels and the rack panels. 

As discussed in Reference 38, experimental and calculational results have indicated that neutron 

channeling effects diminish as the thickness of the neutron absorber increases, given a constant 

volumetric density. Hence, for high areal densities or thicknesses, when the neutron transmission is 

small, the impact of different materials should be small. However, the rate of change in areal density as a 

function of neutron transmission will be different for different materials (Reference 39), resulting in a 

calibration curve that is not representative of the material of interest. Accuracy of neutron transmission 

measurements is very susceptible to the physical properties of the calibration cell standards matching the 

test panels. Based on the limited documentation reviewed, the estimated relative uncertainty associated 

with using different calibration standard materials from the rack cell materials (provided 10B is the 

primary neutron absorber isotope) is estimated to be ±30 percent which takes into consideration existing 

guidance for spent fuel storage and transportation applications regarding credited neutron absorber 

(Reference 40). If a different absorber (e.g., gadolinium) is used, no estimate can be made without 

detailed experimental data. 
30 

For on-site calibration, a standard calibration panel that is identical in all physical properties and 

characteristics as the test panel(s) (i.e., rack designs with corresponding matching “representative” 

calibration panels) is likely to generate the lowest uncertainty. In situ neutron transmission measurements 

are very sensitive to variation in measurement geometry. If “representative” calibration panels for 

reference panels are not available, then uncertainties might possibly be addressed, at a minimum, by 

developing a technical basis document which includes radiation transport-based calculations which can be 

used to supplement the detector response functions to get a better estimate of the bounds. 

5.6.5 Location and Acclimatization of Calibration Cell in Pool 

The information reviewed indicates that the calibration cell is either placed on top of empty rack modules 

(Reference 41, p. 4-10), or next to the rack modules (Reference 35) in the vicinity of the cells being 

tested. This non-standard placement of the calibration cell introduces uncertainties due to background 

radiation and specific environmental effects manifested in the response of the neutron detector. For 

example, an important aspect may be the temperature dependence of the neutron detector efficiency when 

the detector is placed in the pool and then equilibrates in the thermal regions near adjacent spent fuel 

assemblies. Reference 24 provides example detector specification data and states that “at ambient 

temperatures ranging from room temperature to 300°F (149 °C) the thermal neutron sensitivity... shall be 

within ±20 percent of the room temperature value.” Local pool temperatures can vary across different 

regions of the pool. This can result in different levels of mixing from thermal gradients (i.e., local soluble 

boron concentration distribution/stratification) and possible differences between the calibration cell, the 

reference cell, and the test cell environmental conditions. Hence, the uncertainty in the overall response 

functions will change because of environmental influences specific to the pool region in which that test is 

being conducted, and such effects could be minimized by allowing the system to acclimate to the 

conditions representative of the panels to be scanned, so that all measurements are performed under 

similar environmental influence conditions. 

5.6.6 Choice of “Zero-Loss” Panel and Uncertainty of Actual 10B Areal 

Density 

As defined in Section 2, the zero-loss, or zero-dose, panel is the reference panel to which all test panels 

are indexed. The reference panel allows the transformation of the measurement into a percent loss. 

Because the 10B areal density of the reference panel is a key term in the calculation equation (see 

Reference 10) of the 10B areal density of the test panel, uncertainty in the reference panel will affect the 

uncertainty of the overall BADGER output. To mitigate this major source of uncertainty, strict adherence 

to administrative controls must be enforced on the reference panel to ensure that degradation in the 10B 

areal density is zero. The level of administrative controls required for this assurance was not available; 

however, according to the calibration formulations provided in the literature, the neutron transmission 

relationship is deliberately indexed back to the reference panel, linearly. Some of the test campaign 

reports had originally identified no dose panels as being in use but were later determined to have received 

dose; in other instances, reference panels that should not have any losses were observed to have losses. 

Although dose is considered a contributor to absorber loss, especially for Boraflex, there are other spent 

fuel pool environment conditions that can also lead to absorber degradation, such as heat and pool 

chemistry. Hence, all panels will potentially be subject to degradation once inserted into the spent fuel 

pool. Reference 12 indicates that the transmission ratio comparison should be compared against the 

calibration standards directly. 
31 

The principal contributors to uncertainty in actual 10B areal density of the reference panels are a lack of 

detailed records for specific panels, the use of batch processing, manufacturing variability within a given 

batch, and erroneous identification of panel dose. Rack cell panel variations of ±10 percent from nominal 

are typical (Reference 18). 

The reference panel provides the set of BADGER measurements from which a percent degradation value, 

percent D, is calculated according to Reference 34 (Equation 3.3.1): 

%ܦ ൌ ൬

௥ߩ െ ߩ

௥ߩ

൰ 100%

where ρ is the 10B areal density measured in the test panel and ρr is the 10B areal density measured in the 

reference panel. An underestimation of the ρr in the reference panel will result in an overestimate of the 

percent degradation. Consider the following simple example: 

The reference panel is assumed to have a ρr of 0.06 g/cm2

. Suppose a test panel areal 

density, ρ, is measured to be 0.05 g/cm2

 based on the calibration curve. The percent 

degradation is thus calculated to be -16.7 percent. Later, it is realized that the reference 

panel had been degraded because it had been exposed to some external gamma-ray flux 

and was thus not a true zero-dose panel. If the 10B areal density of the true zero-loss 

panel were actually a ρr of 0.065 g/cm2

, then the percent degradation of the test panel 

would be recalculated to be -23.1 percent. The error in the reference panel assumption 

would have yielded a nonconservative result: the percent degradation of -16.7 percent 

was smaller than the true degradation of -23.1 percent.

Based on this example, it is shown that identifying the reference panel areal density correctly and to 

ensure adequate controls are in place to ensure that the reference panel suffers no neutron absorber loss is 

paramount to limiting uncertainty. An 8.3% (0.065-0.06)/0.06 degradation or change in areal density in 

the reference panel which is not detected or known results in a bias of 38% (8.3%/23.1%) in the percent 

degradation value when uncorrected for. 

If the reference panel 10B areal density value is biased (that is, the assumed 10B areal density differs by an 

unknown amount), all examined test panel biases will be of the same sign and magnitude. Additionally, 

the density of the test panel ρ initially increases as the panel undergoes radiation-induced 

shrinkage and subsequently decreases as the panel undergoes dissolution. Therefore, comparing 

the as-is density ρ of the test panel to the density of a zero-loss reference panel density ρr to 

determine if or how much degradation has occurred is problematic and potentially a source of 

uncertainty. 
32 

5.6.7 Nonlinearity of Calibration Curve, Especially as Applied to Flux-Trap 

Racks 

The calibration curve for implementation of BADGER is established by performing a nonlinear 

regression model of neutron transmission on 10B areal density. The ratio of the neutron intensity (count 

rate) in the attenuated region to unattenuated region (I/Io) is equal to an exponential function in the 

parameter ρx, 10B areal density (g/cm2

): I/Io = exp([-Σa/ρ]·ρx), where Σa is the integral macroscopic 

absorption cross section integrated over neutron energies impinging upon the absorber panel, ρ is the 

volumetric density (g/cm3

), and x is the thickness of the absorber panel (cm). Given calibration plates of 

areal density, ρi, for i = 1 to 5, the ratio of count rates in a given detector is regressed on the ρxi values. 

Estimation of the least-squares fit parameters and associated MSE terms must be evaluated and 

propagated through calibration. 

The flux-trap Region I design is subject to an additional uncertainty in the fit parameters given that 252Cf 

source neutrons must penetrate two panels before reaching the neutron detector. The hardness of the 

spectrum needs to be evaluated to ensure that the second panel is not near “infinitely thick” to the 

thermalized neutron spectrum. 

 

5.6.8 Uncertainties in Calibration Slope, Especially as Applied to Flux-Trap 

Racks 

Spectral effects from differing geometry between the actual rack cell and the calibration cell may produce 

a different detector response to changes as a function of areal density. There is some question regarding 

the consistency of the energy distribution of the neutron interrogating flux between the calibration cell, 

the reference panel, and the panels under investigation. It is noted that the slope of the calibration cell 

curve for a flux trap can be extremely steep as a result of the blackness of the neutron absorber, especially 

at higher 10B areal densities. Small changes in the neutron transmission ratio can result in a relatively 

large change in the reported areal density. Therefore, slope errors have a large influence on measured 

areal density. Use of a two-point calibration (min, max) as described in early BADGER test reports 

(Reference 8) assumes that the instrument is linear over the interval of interest. This will increase 

uncertainty for an exponential/logarithmic functional fit because there are insufficient degrees of freedom 

to estimate the MSE in the fit parameters. The calibration functions require further evaluation to 

ultimately determine the various sources of uncertainty in the function. However, the Watt-fission 

spectrum of neutrons emitted from the 252Cf source are down-scattered by the time they reach the first 

panel in a flux-trap design. Neutrons that penetrate the first panel of a flux trap (closest to the source 

head), with sufficient energy to do so, are subsequently down-scattered prior to reaching the face of the 

second panel of the flux trap (closest to the detector head). The down-scattered flux is of such low energy 

that the second panel is under-sampled and thereby overmoderated. Without knowing the degradation in 

the first panel (closest to the source head), there is no way to estimate degradation (or areal density) in the 

second panel (closest to the detector head) of the flux-trap because BADGER takes an integrated 

combined measurement of the entire flux trap. 
33 

Consider the following hypothetical calibration cell consisting of panels A, B, C, and D with known areal 

densities of 0.0212, 0.0148, 0.0085, and 0.0042 g 10B/cm2

, respectively. A subset of simulated count rate 

data was taken from Appendix A, which is representative of the BADGER system for this example and is 

illustrated in Table 5-1. 

Table 5-1. Example calibration cell data 

Panel Areal density 

(g 10B cm-2) 

Counts 

(attenuated)

Counts 

(unattenuated)

T (attenuated/ 

unattenuated) 

A 0.0212 88 386 0.2280 

B 0.0148 99 386 0.2562 

C 0.0085 125 386 0.3239 

D 0.0042 180 386 0.4662 

To illustrate the impact of a two-point calibration, consider panels A and D. Because there are two 

points, the slope is Δy/Δx = m = -0.0237 (note y is areal density and x is ln[T]). Using the areal density 

function relationship described in Reference 10(Eq. 5-1), 

 ρA,ij = ρA,0 + m·ln(Tij) (5-1) 

where 

ρA,ij = 

10B areal density of a test panel, 

ρA,0 = 

10B areal density of the reference panel, 

 m = slope determined from a separate calibration function, 

 Ti,j = the transmission ratio, which is the count rate ratio of the test panel to the reference panel, 

and a reference cell panel areal density, ρA,0, equal to panel A, the test panel scan data with transmission 

ratios corresponding to the B and C areal densities will be in error by 24 percent and 52 percent, 

respectively. As discussed in Reference 10, it appears that over time the use of the calibration cell has 

changed to include more than a two-point calibration. However, the details of how the calibration 

function is determined and ultimately used were unavailable for review. 

An additional uncertainty can be introduced into the calibration function from the count rate data, and the 

uncertainty is more prevalent when the thermal neutron transmission ratio is lower, such as in a flux trap 

design. Considering the discussion on count rate in Section 5.1.1, assume that the calibration is 

conducted with longer count times, and thus higher counts, such that 1 percent Poisson counting error is 

achieved. The test cell scans are conducted quickly, resulting in higher counting error (e.g., 7 percent). 

Neutron transmission is a ratio, so combining the test cell uncertainty results in a combined uncertainty of 

~10 percent approximated by the following relationship: 

ߪ ൌ ܶටቀ

ఙೣ

௫ ቁ

ଶ

൅ ቀ

ఙ೤

௬ ቁ

ଶ

 ؆ 10% ሺݔ ܽ݊݀ ݕ are count rates making up T, 200 for this exampleሻ. 

This represents the combined uncertainty on T, the ratio of x:y. Using the fitted equation in Figure 5.3, 

for a transmission ratio, ln(T), of -0.83, corresponding to an areal density of 0.0092, the areal density 

range is 0.005 g 10B/cm2

, which equates to an uncertainty range of +19 percent to –26 percent. This 

uncertainty would need to be combined with any uncertainty introduced from the slope and can quickly 

escalate. 
34 

Figure 5.3. Representative calibration curve.

5.6.9 Frequency of Calibration during a BADGER Campaign 

Specific calibration frequencies during a BADGER campaign were not available. Reference 37 indicates 

that calibration control measurements should be taken at the start of each day or as often as experience 

dictates. The time between checks can be lengthened if the instrument continues to stay in control. From 

Reference10, it appears that the latter is currently being implemented because the calibration frequency 

during a BADGER campaign is low (i.e., once or twice during a campaign). The low calibration 

frequency is in part due to the experience base developed with the BADGER system for Boraflex racks. 

In lieu of calibration, confirmatory checks are made by comparing the unattenuated region scans of each 

ith panel, and then correcting for measurement “drift” (Reference 10). If the BADGER method is applied 

to neutron absorbers other than Boraflex, that experience is lost, and the uncertainty of infrequent 

calibrations returns. Conducting BADGER calibrations at higher frequencies until equivalent experience 

with the material is gained will reduce uncertainty associated with the calibration frequency. The QC and 

recalibration plan used for ensuring measurement quality is unknown, so no estimate of uncertainty can 

be made. 

5.6.10 Confirmatory Analysis with Destructive Examination 

The purpose of the BADGER system is to perform nondestructive examination of a panel to evaluate 

whether it can still be relied upon for suppressing reactivity. Hence, confirmatory analyses with 

destructive examination are really only available during the design and test phase of the system to assess 

y = 7.48E-04e-2.22x

R2 = 9.92E-01

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0.0300

-1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0

Areal Desnity (10B/cm2)

ln(T)

D

C

B

A
35 

the performance, and build confidence in the analysis capability. Removal of panels for destructive 

examination for comparison purposes after each BADGER test may actually introduce more uncertainty 

into the overall results because of the handling operations. 

Reference 41 (Section 3.2) describes special test cells from which destructive examinations were 

performed to evaluate the condition of the Boraflex. It was not indicated that BADGER scans were 

conducted prior to the examinations. No estimate on uncertainty can be provided at this time based on 

available destructive analysis results.

5.6.11 Panel-Specific Use and Interpretation of Unattenuated Region Data 

In the MCNP validation report (Reference 29), a long count (i.e., minutes) is described as being taken in 

the unattenuated region from which to estimate the “drift” variation in the normalization of the neutron 

intensities between the ith panel measurement to the reference panel. As shown in Figure 5.4 below, the 

unattenuated region at the top of each panel is a several inch region where the neutron absorber is not 

present, but the distance between the BADGER neutron source head and detector head can be held 

constant. In other words, the rack cell wall and wrapper are still interposed between the source and 

detector head but the neutron absorber material is not present. An intercomparison between the detector 

count rate in the unattenuated region of the ith panel to the unattenuated region of the reference panel is 

used to correct for localized drift (Reference 10). No specific information or data has been provided to 

estimate the magnitude of the correction and its associated error. 

Figure 5.4. Representative Region II spent fuel pool storage cell (Reference 34). 
36 

5.6.12 Algorithms to Convert BADGER Trace Data into Input for Calibration 

Curve 

The MSE from the nonlinear or linearized least-squares calibration curve should be used to propagate the 

uncertainty in the areal-density standards, the Poisson error in the count rate of the detector, and any other 

terms that influence the calibration. Areal density is inversely proportional to neutron count rate, by a 1/e

function as derived. 

ܶ ൌ ூ

ூబ

ൌ ݁ିఀೌ௧ (5-2) 

where 

I = neutron counts registered in presence of absorber, 

I0 = neutron counts registered in absence of absorber, 

Σa = macroscopic absorption cross section of absorber, cm-1, 

t = thickness of absorber, cm. 

Neutron transmission, T, is the ratio of I/I0 (the ratio of counts in the attenuated region to the unattenuated 

region). The 10B areal density (g/cm2

), the derived parameter of interest, is the product of the 10B density, 

ρ (g/cm3

), and the thickness of the absorber material, t, in centimeters. This nonlinear relationship is 

linearized in ln(T) and estimated from a linear least-squares regression. Based on a measurement of T, 10B areal density, ρt (g/cm2

), is predicted from the calibration function. As long as all measurement 

conditions are held “constant” between measurements of neutron intensity, a linear least-squares fit of 

neutron transmission versus 10B areal density will result in a calibration function that theoretically could 

be as precise as a few percent. 

Areal densities are derived from the basic detector count rate data by developing a semi-log least-squares 

fit of the natural logarithm of measured neutron transmission, T, against the calibration standard panel and 

reference panel 10B areal densities. When applied to the panel measurement investigation, the areal 

density is calculated from the following function (Reference 8, p. 4-30): 

 10B Areal Density = m·ln(T) + b (5-3) 

where 

T = neutron transmission ratio, 

m = slope of the calibration curve, 

b = intercept with the ordinate (the reference panel). 

The neutron transmission ratio, T, is defined as the average count rate through the absorber region (away 

from gaps) divided by the detector count rate above the absorber region with only stainless steel and 

water separating the detectors from the source. As described in Reference 8 (p. 4-30), the slope, m, is 

determined by measuring T in the calibration cell at two areal densities that bound the tested areal 

densities. The constant b is determined by measuring T in an actual rack cell that has not sustained 

absorber loss (reference panel). A derivation of this basic equation that relates the test panel directly to 

the reference panel was provided in Reference 10(Eq. 5-1), and is also described in Section 5.6.8. 

To minimize uncertainty when developing the calibration curve, the measurement conditions that need to 

be met include (1) neutron background is proven small and/or accounted for; (2) neutron in-scatter into 

the detector assembly is evaluated and corrected for; (3) the total count (number of neutron events 

recorded) is statistically reliable, that is, greater than 5,000 counts per detector per measurement step; 

(4) repeat measurements are conducted during calibration to estimate MSE (Reference 17 recommends at 
37 

least four repeat measurements); (5) the calibration function has calibration points spanning the range of 

areal density of anticipated test panels; (6) the calibration panels are manufactured to within a tolerance of 

less than a few percent; (7) the calibration equation offset (or y-intercept) is forced to 1 (i.e., I/Io is equal 

to 1 when the 10B areal density is zero; and (8) an analysis of variance is conducted to estimate the error 

terms in the calibration function, and whether a weighted least-squares analysis is a better approach to 

reducing the MSE. 

A technical basis document typically contains a systematic parametric evaluation of the calibration 

function describing the mathematical relationship between measured neutron transmission of a test panel 

and the 10B areal density. 

Boraflex Panel Gap size. A separate calibration function, and least-squares analysis, of gap size versus 

count rate has not been provided but is referenced in Reference 18 (NET-287-01, p. 18): “Gap size is 

determined by utilizing a transmission ratio fit derived from calibration cell data ... and ... in addition to 

gaps and cracks, other anomalies were observed.” Reference 8 indicates that the measurement 

uncertainty for gap size is +0.5/-0.0 in. (1.3 cm) for gaps smaller than 2.0 in. (5.1 cm) and +1.0/-0.0 in. 

(2.5 cm) for gaps larger than 2.0 in. (5.1 cm) Uncertainty in gap elevation was reported as ±1.0 in. (2.5 

cm). Reference 18 and several others indicate that BADGER's ability to detect gaps is limited to +1/3 in. 

(0.85 cm) based on experimental evaluations. Cracks were defined as lateral anomalies that are smaller 

than 1/3 in. (0.85 cm) axially, but because cracks are below BADGER's resolution, it is possible that they 

could be regions of local dissolution that do not fully penetrate the thickness of the absorber panel. It is at 

the discretion of the test engineer to distinguish between gaps and cracks when interpreting the test data. 

Boraflex is known to undergo radiation-induced shrinkage, asymptotically approaching 4.1 percent, 

resulting in densification and gap formation (Reference 10). No information was available for review 

describing how the uncertainties between gap sizes and panel densification are accounted for in the 

algorithms for calculating areal density. A description of how the BADGER scan data is interpreted is 

provided in Reference 10(Section 5.2) where it is stated that features such as gaps, local dissolution, 

scallops, etc. are often difficult to characterize in practice. 

Details of the calibration curves used and how the contributing parameter uncertainties are propagated 

forward were not available for review, so no estimate on uncertainty can be made at this time. 

5.7 DATA PROCESSING 

5.7.1 Reliance on Operator Experience to Detect and Characterize 

Heterogeneous Degradation 

Each of the four detector responses is treated independently, with each of the four detector traces (neutron 

count rate or normalized count rate) displayed by the software, such as the trace shown in Figure 5.5, 

which was taken from Reference 35. A plot of normalized count rate for each detector, one through four, 

shows that a gap was detected at 30 in. (76 cm) and 125 in. (317.5 cm), and that once the source/detector 

heads are located at the top of the panel in the unattenuated region ~145 in. (368 cm) to 155 in. (394 cm)), 

the count rate ratio steps up in magnitude by a factor between ~50 and ~130. BADGER relies on a skilled 

technician and engineering operator for implementation, use, and data interpretation so that conclusions 

about the scans can be made. There is also a strong reliance built upon RACKLIFE predictions to aid the 

operator in identifying when the scans are incorrect (Reference 10, Section 4.3.4). It is at the operator’s 

discretion on how to ensure “quality data” is acquired, determine the measurement repeat frequency, 

evaluate whether electronics failed during a measurement, establish mechanical offsets in the adjustment 

of the source and detector heads, and so forth. A discussion on how trace data is analyzed is provided in 

Reference 10(Section 5.2). 
38 

Figure 5.5. BADGER detector traces (Reference 35). 

High uncertainty can be introduced in the results as a result of operator interpretation, especially 

regarding decisions on censoring data. Some examples identified in BADGER test reports indicated that 

due to system noise, results from certain detectors were considered unreliable, but the scans from the 

other detectors were still used. The data trace plots showed a clear offset from the rack cell descriptions 

and significant variability in length. To minimize the uncertainty of operator interpretation, standardized 

decision processes could be developed for incorporating feedback (Section 5.7.3) when a change in 

condition is observed. 

Reference 10 indicates that the experience of the operator and the analyst is a strong determinant in 

reducing uncertainty and discusses how they need to attune themselves to be able to characterize 

BADGER scan results. There was no information available regarding the training and qualification 

requirements for the operators or analysts; therefore, it is not clear how this uncertainty is controlled. 

Reference 42 indicates that to make quality NDA measurements, training of measurement personnel is 

required, and that the level of training needed is dependent upon the complexity of the measurement 

technique and the responsibilities of the personnel. An example good practice guide for training and 

qualification of NDA personnel is available in ASTM C1490-04, Standard Guide for the Selection, 

Training and Qualification of Nondestrucitve Assay (NDA) Personnel (Reference 42) that may be 

beneficial to reducing uncertainties associated with interpreting BADGER scan data. 

Mathematical data reduction for the averaging of all raw data would need to be presented in order to 

propagate uncertainties to a total measurement uncertainty. For example, Reference 8 (Section 3.2.2) 

states the following: “In regions containing a gap, all counts in excess of 3 sigma of the mean count rate 

in the region without gaps are not considered in determining the panel areal density.” The basis of this 

statistical approach for characterizing a given panel was unavailable to be examined. Additionally, it was 
39 

not clear that the methodology includes rejecting count rates that fall below three sigma of the mean count 

rate when determining the panel areal density. To produce low uncertainty results, the data reduction 

algorithm needs to incorporate consideration of the following mathematical constructs: (1) how each 

detector, i = 1 to 4, is evaluated individually, and then summed or averaged for purposes of gap detection; 

(2) how mean and standard deviation are calculated for each detector, for each panel-segment response, 

and for each panel; (3) how the background is measured and interpreted for determining the mean 

transmission and associated standard deviation, at which the 3-sigma decision is made; and (4) how repeat 

measurement results replace or add to the “bulk” statistical quantities, i.e., sampling with or without 

replacement. Detector spatial resolution evaluations would be needed to examine what gap detection 

width is allowable and whether the four-detector assembly is sufficiently sensitive to this width, at the 

3-sigma decision point, or the equivalent/improved statistical method for detecting and reporting gaps. 

The following information would be needed for review to quantify the uncertainty associated with the use 

of reduced statistical data on an individual, measured panel (number of gaps, gap width, and average 10B 

areal density) to infer or predict the performance of BADGER for a whole panel: (1) the statistical 

selection methodology for which n of N panels are measured; (2) a description of the propagated 

measurement uncertainty in each panel measurement; (3) a description of the algorithm used to 

calculate average panel 10B areal density from local data points, given heterogeneous 

degradation; and (4) a statistical methodology for combining sampling error and measurement error. 

5.7.2 Applicability of Boraflex-Based Algorithms to Non-Boraflex Material 

Such as Boral® or Metamic 

No information was available regarding algorithms except the basic derivations from the attenuation 

relationship. However, the application of BADGER scan data and the panel selection process is highly 

focused to support use of RACKLIFE, which is Boraflex specific and not applicable to other materials. 

The formation of anomalies in non-Boraflex materials and impacts to the localized geometry of the 

measurement will significantly impact the count rate of neutrons transmitted through the neutron absorber 

and will need development of material-specific algorithms for proper characterization and identification. 

5.7.3 Feedback Procedure 

For the operations and use procedure, clear specifications for registering information and data on any 

physical conditions of a given segment measurement that could cause a “change of condition” allows 

identification of when the results may no longer be valid or an adjustment needs to be made. A “change 

of condition” such as a spent fuel pool region with a better or worse mixing region which could affect 

soluble boron concentration, significant panel batch differences, test panel areal density outside range of 

calibration, or other changes, could mean that the calibration curve, or assumptions used in the 

development of it, is invalid. Some feedback into or correction of the data set would need to be 

developed to ensure that the number of repeat measurements is minimized and that data censoring is 

appropriate. Several reports indicate that there are sizeable operator issues with the conduct of the 

measurements. 

To minimize uncertainty and promote repeatability in future BADGER scans, operator experience and 

system adjustments should be captured for future use. For example, operator responses to key 

measurement parameters can be written into the measurement logbook and evaluated to determine 

conditions that would invalidate the calibration and test assumptions. Another effective method for 

ensuring that measurement results are repeatable and stable is to select a subset of measurements and 

conduct a repeat measurement. This approach is commonly utilized in other NDT applications. The 

sample repeats may be selected in regions of the test where difficulties may have been encountered or 
40 

there is some question in the examiner’s mind that the measurement may have been compromised or in 

error. Sample repeats may also be selected at random to test and ensure system performance. A 

combination of resampling approaches may be developed. 

5.8 STATISTICAL EXTRAPOLATION AND SURVEILLANCE 

FREQUENCY 

5.8.1 Choice of Test Panels to Survey 

The information reviewed, which is primarily based on Boraflex degradation, indicates that the panel 

selection process has been biased toward supporting RACKLIFE. The actual panel selection process to 

survey with BADGER was unavailable for review, but based on the information available in the test 

reports, the distribution of the selected sample set typically attempts to include a range of panel 

exposures, including what is considered to be the most severe exposure history based on dose and time in 

service as well as a number of panels that are not expected to show degradation. Note that RACKLIFE 

estimates degradation based on several factors in addition to dose and time in service (e.g., silica content 

in solution), which is further explained in Reference 10. This panel selection process is consistent with 

the objectives for assessing overall spent fuel pool absorber conditions but is not conducive to assessing 

panel characteristics for criticality safety analyses because the distributions are convoluted with low 

degradation and high degradation information. Because RACKLIFE was developed specifically for 

Boraflex, it may introduce additional uncertainties if it is used for panel selection for other neutron 

absorber materials (e.g., Boral®). No uncertainty estimate can be made as this is site specific and 

contingent upon how the BADGER data is collected and applied. 

5.8.2 Lack of Duplicate Scans of the Same Test Panel 

Duplicate BADGER scans can be used within a single measurement campaign or in subsequent 

campaigns to determine in situ measurement reproducibility and to spot trends in the overall performance 

of the device. 

A very limited number of panels are scanned in subsequent campaigns, which would be beneficial for 

evaluating trends. Because of system modifications and large uncertainties in earlier campaigns, the 

limited repeat panel data is unreliable for trending analyses. This is due to the selection of too few panel 

samples, improper calibration, and system modifications between campaigns. For example, if the 

reference panel 10B areal density, i.e. the y-intercept b of Equation 5.3, was inaccurate, then all of the test 

panel areal densities would be biased, causing the average across one campaign to be different from the 

next in unexpected ways. If, instead, the slopes based on the calibration cell were inaccurate, then local 

degradation could be accentuated with large calibration slopes. That is, one campaign could observe local 

dissolution due to large slopes yielding variations in count rate that lead to large computed variations in 

areal density, while another campaign would observe more uniform dissolution due to small slopes 

yielding variations in count rate that lead to small computed variations in areal density. This indicates that 

the calibration is perhaps the most important aspect for BADGER operation. 

An example of how process uncertainty is associated with the gap identification protocol is provided in 

Reference 15 (Part 2: NET-229-01). Panel rescans of the same panel from opposite directions were 

conducted in an attempt to increase the precision of the results for the rescanned panels. It was indicated 

that most of the rescans showed good correlation between the two scans. However, one pair, U11 

East/V11 West, showed variability in the interpretation of local anomalies. One scan showed six gaps 

with a maximum size of 1.96 in. (4.96 cm), while the other showed five gaps with a maximum size of 

5.16 in. (4.98 cm). This indicates an uncertainty range of 24 percent to 32 percent in gap size 
41 

identification if two 1.96 in. (4.98 cm) gaps were combined in the second scan compared to the 5.16 in. 

(13.1 cm) gap. The difference in these results is likely due to a slight neutron spectral shift through the 

steel cell wall before traversing through the neutron absorber material and into the detector tubes 

compared to the scan in the other direction. This method is not consistent with Reference 12, which 

indicates that neutron attenuation measurements shall use the same test equipment and configuration. 

Reversing the orientation of the probes changes the configuration and effectively invalidates the original 

calibration function. 

5.8.3 Application of Results of Selected Panels to Entire Pool 

The number of cells in a spent fuel pool may number in the thousands. Thus, not all panels are measured. 

Rather, a small subset of panels is selected for NDT, based on in-service knowledge about the panels—for 

example, from the total integrated gamma-ray dose to the panel and an estimate of 10B loss based on inservice history from the RACKLIFE software for Boraflex. 

The actual panel selection process to survey with BADGER was unavailable for this review, but based on 

the information provided in various test reports, the distribution of the selected sample set typically 

attempts to include a range of panel exposures, including what is considered to be the most severe 

exposure history based on dose and time in service as well as a number of panels that are not expected to 

show degradation. The majority of the test panel data reflects a selection process designed to provide 

confirmation of the RACKLIFE code predictions and for developing future projections as illustrated in 

Reference 10(Figures 4-9 and 4-10), which is consistent with the initial development objectives 

established in the mid-1990s. The panel results are then used to update the RACKLIFE predictions for 

characterizing the other panels in the rest of the spent fuel pool. RACKLIFE 10B areal density loss 

algorithms are only applicable to Boraflex degradation as described in Reference 10 and are not 

applicable for other types of neutron absorber materials. 

To date, in a number of test campaigns, the number of panels preselected for testing was reduced in 

number during the testing because of time constraints. For example, Reference 18 had preselected 45 

panels for evaluation but actually scanned only 32. Other test campaigns show panel measurement data 

being rejected with no explanation. It is not clear how these changes in the test sample population are 

being conducted while preserving an adequate sample population that is representative of the panels in the 

pool. 

Without knowing local conditions of neutron absorber degradation in a spent fuel pool, a specific 

statistical sampling method cannot be prescribed. There are several common methods to select from, in 

order to minimize the sample size, N, yet keeping the MSE reasonably small to meet performance 

objectives for evaluating overall pool performance. Biased or random sampling can be used depending 

on project objectives. Several statistical sampling and test methods have been used for the analysis of 

sampled data in nuclear operations: (1) lot tolerance percent defective, (2) complete block design, (3) 

randomized complete block design, and (4) stratified random sampling, to name a few. Controls can be 

used to ensure that the sample design and outcome of the measurement results satisfy the selected method 

assumptions and constraints before statistical results can be reported for the projected performance of the 

entire pool, (e.g., number of gaps per panel, gap size per panel, and minimum 10B areal density). 
42 

5.8.4 Frequency of BADGER Campaigns, Especially for Panel Materials 

Where Intermediate Calculational Methods Such As RACKLIFE Are 

Unavailable 

For neutron absorber materials where methods to predict panel degradation between BADGER 

measurement campaigns is not available, the frequency of campaigns should be determined on the basis 

of the known or projected degradation rate, and the margin between the minimum projected 10B areal 

density and the value used in the criticality analysis. A graded approach to measurement frequency could 

be used. Historically with BADGER, estimated degradation rates were generated using the RACKLIFE 

software. In many applications where Boraflex is not the neutron absorber being evaluated, RACKLIFE 

is not applicable, and therefore other means would need to be developed in conjunction with estimating 

poison panel degradation in order to more accurately determine the optimum frequency for the use of 

BADGER. 

5.8.5 Application of Final Output to Criticality Analyses of Record 

NETCO has developed a method for incorporating the BADGER scan results into an assessment of the 

reactivity effects of local panel degradation utilizing Monte Carlo sampling techniques (Reference 18, 

p. 40). Details of the method were unavailable for review, but partial descriptions are provided in 

Reference 43 (Section 4.0 in NET-173-01) and Reference 44. Note that Reference 43 was developed in 

2001, and subtle differences were observed in the description of implementation provided in Reference 

44, which was written in 2010. Therefore, it is not clear if there are multiple methods or the method as 

described has changed, and hence, no definitive conclusions could be made regarding application of the 

BADGER scan data to the criticality safety evaluations of record. 

In general, from the partial descriptions reviewed, the method(s) can be summarized as random sampling 

of panel local degradation features from BADGER scan data that are used to simulate rack panel 

conditions in a representative reactivity equivalence model. Because criticality is a local phenomenon, 

care must be taken with how the localized conditions associated with panel degradation, gaps, cracks, and 

anomalies as well as associated uncertainties are incorporated into the representative reactivity 

equivalence model. Therefore, the following observations are provided for consideration regarding 

application of BADGER scan data to criticality safety evaluations. 

1. The description provided indicates that each panel is being treated independently for simulation 

in the reactivity equivalence model. It is not clear that correlations between highly degraded 

panels or large gaps collocated in the same rack cell region are being accounted for in the Monte 

Carlo sampling process. For example, a panel that experienced high dose at some point in time 

was in a cell that had other panels that would have also been susceptible to receiving high dose at 

that time. Therefore, a correlation would exist for high loss panels on a per rack cell basis. 

Observations of the panel trace data in the reviewed BADGER test reports showed several 

instances where gaps are present at nearly the same axial elevation for multiple panels within the 

same rack cell (e.g., rack cell AA27 of Reference 18 and C6 of Reference 35). Typically, all four 

panels of a cell are not tested, but because the panel scan data is being treated independently in 

the reactivity equivalence model, correlations do not appear to be accounted for in this method. 

2. The description of the method provided in Reference 43 indicates that the reactivity equivalence 

model is simulated multiple times to establish a distribution of keff calculations from which an 

estimated bounding value at a 95 percent probability for a 95 percent confidence interval is 

selected. Details of how this is being performed were not available for review, but depending 
43 

upon how biases are incorporated into the sampled panel degradation distributions, the use of the 

maximum keff plus two-sigma may be more appropriate. 

3. Panel absorbed dose and B4C loss predicted by RACKLIFE algorithms specific to Boraflex 

degradation are used as input parameters for panel selection and distribution within the reactivity 

equivalence model. Hence, the current panel selection process and methodology would not be 

appropriate for application to other neutron absorber materials (i.e., materials other than 

Boraflex). 

4. The calculations of the panel areal density accounts for two major sources of uncertainty in the 

testing process, namely, measurement uncertainty and statistical uncertainty (Reference 35, 

Appendix C). An analysis of the uncertainty associated with the distribution fit function(s) also 

should be included. 

5. An additional uncertainty component which is especially important in applications where 

RACKLIFE is not applicable, is to ensure that panel selection is based on a statistically valid 

sampling plan that accounts for both sampling and measurement error and includes consideration 

of potential correlations in sample results. 

6. An additional uncertainty which can be introduced into application of the BADGER scan data is 

process implementation variability. For example, Reference 43 (Section 4.0 in NET-173-01) 

indicates that the base case represents the Boraflex panel at its minimum certified areal density 

and thickness, whereas in Reference 16 (Section 4.0) it was indicated that the base case is based 

on the nominal areal density and thickness. The latter results in an additional bias that needs to 

be accounted for in the criticality safety evaluation.

5.8.6 Use of Final Output in Abnormal or Accident Sequence Criticality 

Analyses

Consistent with the requirements of 10 CFR 50 Appendix A GDC 62, “Prevention of Criticality in Fuel 

Storage and Handling” (Reference 2), the spent fuel pool must remain subcritical at all times. Hence, the 

0.95 keff subcritical limit (10 CFR 50.68) must also be maintained for abnormal or accident scenarios. A 

potential outcome of a seismic event, dropped fuel assembly, or other load on a rack module containing 

degraded absorbers is the movement of the remaining Boraflex or other neutron-absorbing material. Such 

movement can potentially resulting in alignment and/or enlargement of gaps within a rack cell or groups 

of cells leading to an increase neutron transparency. No information was available for review about how 

this is addressed in the criticality analyses. 

 
44 

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45 

6 SUMMARY 

A Type B uncertainty analysis (Reference 17, NIST Technical Note 1297) was conducted on BADGER, a 

NDT instrument that measures neutron attenuation in spent fuel panels in situ. The uncertainty analysis 

methodology used has become known as GUM, the ISO “Guide to the Expression of Uncertainty in 

Measurement.” A Type B analysis is based on scientific judgment using all relevant information 

available, with the recognition and understanding that available information may be, and probably is, 

limited. There are no BADGER-specific consensus standards in existence that describe the calibration 

protocols and functions, the determination of the calibration offset, i.e., the zero intercept, for the 

reference panel, or the recommended QC tests specifically required. 

The accuracy of the BADGER neutron absorber measurement system is primarily a function of 

• the equipment’s ability to discriminate between the radiation of interest and the background 

radiation field, 

• the quality of the equipment calibration and subsequent equipment operation, 

• the consistent and reliable positioning of the neutron absorber between the source head and 

detector head, and

• the ability of the operator to properly use the equipment and interpret the data. 

Standards are available that describe in concise ways how nuclear instrumentation should be functionally 

checked: for example, IEEE N323A-1997, “Radiation Protection Instrumentation Test and Calibration, 

Portable Survey Instruments” (Reference 45). 

This section provides a summary table of parameters that can impact the measurement performance of 

BADGER. Each of the individual parameters was grouped into categories reflecting different aspects of 

the BADGER system and how the results are used. Details of each parameter are presented in Table 6-1, 

but the reader is cautioned that it may not be possible to combine reported uncertainties in a meaningful 

and useful way. 

Table 6.1 consolidates the measurement parameters that give rise to uncertainties in the use and 

application of BADGER. The parameters are grouped into eight categories corresponding to the 

Section 5 discussion. The headings of the table columns are defined here, and some notations are 

explained. 

Section: Section of the report where the measurement category was discussed in detail. 

Measurement category/subsection: Category of the measurement system and subsection 

discussed. 

Physical influence parameter: Physical parameters or characteristics for each measurement 

element. These parameters are the specific detailed influence factors that affect measurement 

bias and uncertainty. An example is neutron count rate in a detector. As the count rate increases, 

measurement uncertainty improves. 

Information used to support discussion: Primary source(s) of information used to support 

estimate of uncertainty described as follows: 

• Expert Judgment – Much of the BADGER system design and test information is 

company proprietary or undocumented. The value reported for uncertainty, consistent 
46 

with a Type B uncertainty analysis, is based on expert elicitation and professional 

judgment by experienced subject matter experts in NDT using in situ neutron 

transmission and attenuation (i.e., the authors of this report). Note that any information 

provided based on expert judgment has an inherent assumption that the BADGER 

system, implementation, and use are consistent with applicable industry codes and 

standards and proper QA/QC principles have been applied. 

• Proprietary Information – This notation is used to identify proprietary data that is 

available to the NRC, but not available to the public. 

• Publicly Available – This notation is used to identify data and reports that are publicly 

available. 

• First-Principle Computation – The authors have calculated from Monte Carlo analysis 

or first principles the magnitude of a reported error term. First-principle computations 

are used to estimate the relative level of uncertainty in a given parameter. 

• No Information Available – No reports or data are available with expressly written 

statements on a parameter-by-parameter evaluation of bias or uncertainty terms. 

Comments regarding relative uncertainty: Summary discussion about the measurement 

parameter of influence and reflection about the vetted relative uncertainty value for each 

measurement element (or group). 

Primary reference source: Citations from which the relative uncertainty value was obtained or 

derived. 

Uncertainty range: Uncertainties are binned into three categories: 

1. For individual parameters supported by first-principle calculations or test data, 

quantitative relative uncertainty values are presented. 

2. For parameters where expert judgment was used as in a Type B analysis, uncertainties 

were given a designation of “low” or “high.” 

a. Values identified as “low” are considered to be small in comparison to the 

other overall contributors to uncertainty and considered to have ~2 percent 

uncertainty or less. 

b. Parameters with values identified as “high” can contribute an uncertainty so 

high as to potentially invalidate results alone, even if all other parameters were 

of low uncertainty. 

3. The designation INQ indicates that insufficient data was available for review to support 

quantifying an uncertainty range for a given parameter. 

Examples of the types of data which, if provided, may yield enough information to produce an 

uncertainty, or calculate a more precise uncertainty, are listed in brackets. 

 
47 

Table 6-1. Summary table of measurement system sources of uncertainty 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

5.1 Neutron Source 

 5.1.1 Count rate Publicly 

available 

No experimental data provided to estimate impact of parameter on overall uncertainty on implementation of BADGER. With reported count times per axial measurement of 10 seconds, the net count rate of 1,000 net counts per count interval gives a relative error of roughly 3 to 4%, neglecting contribution from background. Relative error of Poisson counting statistics given by the relative error in subtracting background count rate from gross count rate, adjusted for any effect associated with pulse pile-up, or variability in the in-scatter from neutrons not originating from the 252Cf source and transmitted 

directly through the Boraflex. From looking at traces of count rate data published in Reference 8, count rates appeared to be ~200 neutron counts per 10-sec interval (sometimes less), in which case the Poisson error is on the order of 7–8% and will increase based on other neutron count rate effects mentioned above. These effects require additional evaluation.

Reference 8 (Figures 3-16 and 4-10) 

 5.1.2 Source strength 

and decay 

No information available 

No information available on source strength. The half-life of 252Cf = 2.65 years, which yields ~0.7% 

change per 10 days. Corrections and adjustments for source decay should be accounted for in the calibration and on-site QC measurements with normalization correction made accordingly 

Reference 23 

 5.1.3 Neutron 

moderation by covers on heads 

No information available 

No experimental data provided to estimate impact of parameter on overall uncertainty on implementation of BADGER. This is likely to be a large contribution to uncertainty to invalidate results for Region I racks, in particular, where the system is overmoderated and the irradiating neutron flux on the second panel of two is thermalized to such an extent that the 10B areal 

density is infinitely thick to the flux. 

N/A 
48 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

5.2 Detector characteristics

5.2.1 Size No information 

available

Performance Specification reflected in count rate (Section 5.1.1) and panel coverage (Section 5.5.5)

N/A 

 5.2.2 Efficiency No information 

available 

Performance Specification reflected in count rate (Section 5.1.1) 

N/A 

 5.2.3 Fill gas 

pressure 

No information available 

Performance Specification reflected in count rate (Section 5.1.1) 

N/A 

 5.2.4 10B enrichment 

of the gas 

No information available 

Performance Specification reflected in count rate (Section 5.1.1) 

N/A 

 5.2.5 Aging Expert judgment QC to maintain within design limits. If unaccounted 

for, results are unreliable. 

Reference 8 and Reference 24 
49 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.2.6 Wall material No information 

available 

Different wall materials will result in different scattering and absorption rates, and can also contribute to background counts. 

N/A 

5.3 Interference 

 5.3.1 Background 

neutron flux from surrounding assemblies 

No information available 

There is no evidence that either engineering controls and/or administrative controls are used to understand, measure, and evaluate background neutron count rates. Background in this case refers to neutrons entering the detector(s) from other adjacent spent fuel assemblies and not to "background" neutrons reflected or inscattered from the 252Cf transmission 

source. 

N/A 

 5.3.2 Gamma 

interference 

Expert judgment Contingent on the operator and on the manner in 

which the nuclear electronics are adjusted in situ to account for gamma-ray pileup pulses that exceed the lower-level discriminator setting on the Single Channel Analyzer (SCA). Low (~2%) if properly accounted for, or results could be unreliable if not properly accounted for. 

N/A 

5.4 Electronics 

 5.4.1 EMI 

susceptibility 

No information available 

Instrumentation technical performance specifications not provided. 

N/A 

 5.4.2 RF pickup No information 

available 

Instrumentation technical performance specifications not provided 

N/A 
50 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.4.3 Amplifiers, 

discriminators, power supply, acquisition board 

No information available 

Instrumentation technical performance specifications not provided 

N/A 

 5.4.4 Signal 

processors 

No information available 

Instrumentation technical performance specifications not provided 

N/A 

 5.4.5 Discriminators 

for pile-up rejection, wall effect 

No information available 

Instrumentation technical performance specifications not provided 

N/A 

 5.4.6 Dead time No information 

available 

Instrumentation technical performance specifications not provided 

N/A 

5.5 Apparatus geometry 

 5.5.1 Head 

misalignment 

First-principle computation 

Because the proximity between the source head, panel, and detector is close (< 6 in. [15.2 cm]), and it 

has been reported that BADGER sticks (or jambs) in some warped panels, the measurement geometry is likely not consistent throughout a single panel (see other parameters below) 

Monte Carlo calculations conducted by authors in Appendix A 

 5.5.2 Rack cell fit No information 

available 

Mitigated for with Section 5.5.1 and 5.5.3. Design element reflected in Section 5.5.5.

 N/A 

 5.5.3 Compression 

springs, shims, vertical offsets 

No information available 

Uncertainty reflected in Section 5.5.1. N/A 
51 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.5.4 Effect of rack 

cell deformation: panel cladding bulges, collisions with assemblies 

Expert judgment Uncertainty similar to Section 5.5.1 across an axial 

segment due to (1) broad beam irradiation of point 

252Cf source across panel surface 2–3 in. (5–7.6 cm) 

from source; (2) detectors ~0.5 in. (1.3 cm) from panel; and (3) bulges reported with dimensions of 1⁄4 in. (0.6 cm) or more. Neutron transmission measurements are very sensitive to these changes in measurement geometry.

 N/A 

 5.5.5 Determination 

of detector coverage of panel area 

No information available 

Design element to meet performance specification. A broad-beam point source projection across a panel surface 2–3 in. (5-7.6 cm) from source is subject to specific measurement controls placed on the uniformity of the irradiation. Uncertainty can be quite high, as opposed to a uniform, "pencil-beam" irradiating flux used in a laboratory-grade couponsample analysis (ex situ).

 N/A 

5.6 Calibration 

 5.6.1 Number, range, 

and precision of 10B areal 

density of standard panels 

No information available 

Not known whether the BADGER calibration function extrapolates beyond the smallest 10B areal 

density provided in the calibration panel. Since a logarithmic exponential function is fit to the calibration data, it is recommended that at least three calibration densities be run above the required minimum areal density, and two below. 

 N/A 

 5.6.2 Standard panel 

degradation 

No information available 

Low if specific administrative controls are in place to ensure that the standard panel does not suffer degradation. If necessary administrative controls are not in place, the bias in the BADGER measurement is directly proportional to the amount of loss in the standard panel. 

 N/A 
52 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.6.3 Adjustment of 

calibration procedure for specific pool characteristics 

No information available 

Unknown effects of local pool characteristics on measurement uncertainty, relative to both the baseline calibration and to the site-specific calibration. 

 N/A 

 5.6.4 Relevance of 

standard panel material to rack panel material, e.g. using a Boraflex calibration assembly to measure Carborundum or Boral®. 

Expert judgment Neutron channeling effects diminish as the thickness 

of the neutron absorber increases. During the calibration scan of panel segments of different thicknesses, the rate of change in areal density as a function of neutron transmission will be different for different materials. 

References. 38 and 40 

 5.6.5 Location and 

acclimatization of calibration cell in pool 

No information available 

Unknown. However, system response will likely vary with temperature. 

 N/A 

 5.6.6 Choice of 

“zero-loss” reference panel and uncertainty of actual 10B 

areal density 

No information available 

The reference panel, also referred to as zero-loss panel, is used as the y-intercept index to all other panels. Whether from a manufacturing tolerance on the reference panel or the misrepresentation of zeroloss, if the reference panel value is biased, all examined panel biases will be of the same sign and magnitude.

 N/A 
53 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.6.7 Non-linearity 

of calibration curve, especially as it applies to fluxtrap racks 

No information available 

Actual BADGER calibration data is not provided. 

Available reports use, for illustration purposes only, the exponential curve fit of detector count rate versus the known characteristic, 10B areal density, from the 

calibration panel. The 10B areal density range of 

calibration panels should extend beyond all likely panel densities, with at least three calibration densities above and two calibration densities below the minimum 10B areal density credited in the rack. 

Sample exponential fits (and associated fit error) are shown in the text of Section 5.6.8.

N/A 

 5.6.8 Uncertainties in 

calibration slope, especially as it applies to fluxtrap racks 

Expert judgment The Watt-fission spectrum of neutrons emitted from 

the 252Cf source is down-scattered by the time it 

reaches the first panel in a Region I (flux-trap) design. Neutrons that penetrate the first panel, with sufficient energy to do so, are subsequently downscattered prior to reaching the face of the second panel. The down-scattered flux is of such low energy that the second panel is under-sampled and thereby overmoderated. Without knowing the degradation in the first panel, there is no way to estimate degradation (or areal density) in the second panel of a flux-trap design.

 N/A 

 5.6.9 Frequency of 

calibration during a BADGER campaign 

No information available 

The QC and recalibration plan used for ensuring measurement quality is unknown. 

 N/A 

 5.6.10 Confirmatory 

analysis with destructive examination 

No information available 

Unknown in the literature how many confirmatory and validation measurements are conducted between the BADGER in situ measurements, and the collection of coupon samples, for subsequent laboratory analysis. 

 N/A 
54 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.6.11 Panel-specific 

use and interpretation of unattenuated region data 

No information available 

Reports cited discuss a "drift" correction (see Reference 10), but it is unclear how this drift correction is conducted. 

 N/A 

 5.6.12 Algorithms to 

convert BADGER trace data into input for calibration curve 

No information available 

Details of the calibration curves used and how the contributing parameter uncertainties are propagated forward were not available for review, so no estimate on uncertainty can be made. 

 N/A 

5.7 Data processing 

 5.7.1 Reliance on 

operator experience to detect and characterize heterogeneous degradation 

Expert judgment Current experience is predominantly based on 

Boraflex and reliance on RACKLIFE as an aid to identify what is being observed. Until an equal experience base can be developed for recognizing the degradation features of neutron absorbers other than Boraflex, the uncertainty in scan interpretation will be high. 

 Reference 10 

 5.7.2 Applicability of 

Boraflex-based algorithms and experience to non-Boraflex material such as Boral® or 

Metamic, which experience different degradation mechanisms 

Expert judgment The formation of localized scallops and blisters in the 

localized geometry of the measurement will significantly impact the count rate of neutrons transmitted through the neutron absorber. 

 N/A 
55 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.7.3 Feedback 

procedure 

No information available 

Process control issue N/A 

5.8 Statistical extrapolation and surveillance 

frequency 

 5.8.1 Choice of test 

panels to survey 

No information available 

The statistical basis for selecting a subpopulation of panels to inspect by BADGER is not known. To some degree, RACKLIFE is used to estimate the most degraded panels, and then this estimate is used to estimate the nominal and worst case conditions for neutron absorber degradation. 

N/A 

 5.8.2 Lack of 

duplicate scans of the same test panel 

No information available 

Unknown. However, duplicate scans provide a means to increase confidence in the estimated uncertainty range. 

 N/A 

 5.8.3 Application of 

results of selected panels to entire pool 

No information available 

Not an artifact of BADGER instrumentation; but a process issue. 

 N/A 
56 

Section Report subsection

Physical 

influence 

parameter

Information 

used to support 

discussion Comments regarding relative uncertainty

Primary 

reference 

source 

 5.8.4 Frequency of 

BADGER campaigns, especially for panel materials where intermediate calculational methods such as RACKLIFE are not available 

No information available 

Unknown. Should start with high frequency until adequate experience base is developed to reduce 

frequency.

 N/A 

 5.8.5 Application of 

final output to criticality analyses of record 

No information available 

N/A: Site specific N/A 

 5.8.6 Use of final 

output in abnormal or accident sequence criticality analyses 

No information available 

N/A: Site specific N/A 
57 

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58 

7 CONCLUSION 

This report documents sources of uncertainty in measurements of the Boron-10 Areal Density Gauge for 

Evaluating Racks (BADGER). The system was designed, assembled, and tested in the early-to-mid 

1990s as a nondestructive scoping tool to evaluate neutron absorbers placed in spent fuel racks for 

confirmatory analyses of RACKLIFE predictions. As discussed in Section 2, available reports that were 

reviewed indicate use of a heuristic deployment strategy. The initial development and deployment effort 

of this tool was unable to benefit from some of the more recent advancements since 2001 in the areas of 

neutron detectors, signal-chain processing, and data acquisition systems for conducting in situ 

measurements that could reduce TMU. It is not known whether a systematic, parametric uncertainty 

analysis of the BADGER system has ever been performed. Hence, it is difficult to forecast what the net 

mean bias and precision truly is for any given deployment of the system. Estimates of uncertainty are 

provided in this report on the basis of many years of experience conducting neutron measurements and 

writing ANSI, ASTM, ISO, and IEC standards on the conduct of radiation measurements for NDA and 

NDT systems. Uncertainty terms were identified and discussed. Estimates for contribution to uncertainty 

were made to reflect potential magnitude. 

Calculation of a TMU or the combined uncertainty of a measurement system requires a complete and 

thorough understanding of the interrelationships of the individual constituents. The BADGER estimated 

areal density values are determined through a series of constituent parameters through a functional 

relationship, which was not available for review. Consistent with Reference 17 and other good practice 

guides, when reporting a measurement result and its uncertainty, a list of components/factors that can 

affect the measurement results, such as that provided in Section 6, and a detailed description of how each 

component uncertainty was evaluated are necessary. The summary listing of constituent parameters 

provided in Table 6-1 is not all-inclusive, as important elements associated with BADGER design and 

implementation were unavailable for review, but it illustrates many of the necessary considerations that 

would need a thorough assessment and review for acceptance in the NDT professional community as a 

quantitative NDT tool. Because of limitations and constraints affiliated with obtaining test reports, 

procurement specifications, BADGER system technical specifications, and operating procedures 

(including those for QC), uncertainty of individual components listed in Table 6-1 could not be estimated 

with the exception of a limited few. 

To develop detailed uncertainty estimates of a quantitative NDT device, the following need to be 

available for review: (1) a technical basis document describing in detail the neutron detectors, collimator 

assemblies, nuclear electronics, data acquisition systems, and algorithms; (2) an instrument qualification 

test plan to implement system specifications for range of use; and (3) appropriate electronics testing and 

labeling as having met specific instrument standards such as IEEE, CE, or UL. Additionally, a peerreviewed document that the instrument will meet its intended purpose and application of use, up to and 

including the publication of a test standard, e.g., ASTM aids in developing the pedigree of the NDT 

device. 

In the case of the BADGER system deployment, it is not clear if the systematic biases have been 

evaluated and corrected, as suggested in practice by ASTM C1592M-09 (Reference 16). As a result, a 

total propagated uncertainty analysis cannot be performed. The root MSE cannot be estimated, and 

summing the relative error terms is not appropriate. Monte Carlo radiation transport calculations 

documented in Appendix A show that the influence of individual parameters could be in excess of ±40 

percent on reported average areal densities. Thus, there is the notion that the total uncertainty could be 

much greater. When a more rigorous evaluation of the influence factors has been performed and made 

available, subsequent corrections to the algorithms made, and all deployment issues proven acceptable, a 

technically defensible estimate of TMU can be calculated and represented. 
59 

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60 

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61 

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62 

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A-1 

APPENDIX A

REPRESENTATIVE BADGER SCAN USING MAVRIC 

 
A-2 

This appendix provides a representative BADGER test to demonstrate some of the impacts on 

measurement uncertainty. A surrogate BWR rack configuration was developed with the MAVRIC 

radiation transport sequence in SCALE (Reference A.1) to generate a representative calibration curve to 

observe the relative effects that minor changes, such as twist and offset misalignment, or calibration cell 

error can have on neutron transmission ratios and the effect on predicted areal density results. The 

MAVRIC model output results are presented in Appendix B for the different model configurations, and 

an example MAVRIC model input file is provided in Appendix C. 

The surrogate BWR rack model is illustrated in Figure A.1. Water has been hidden in the drawing to 

facilitate visualization of cell components. Note that there are several variants of BWR spent fuel pool 

storage racks that could have been modeled, but the model for this report is provided to be representative 

of a typical BWR Region II storage rack and is not specific to an actual design. Each fuel storage rack 

cell is modeled as a square tube of steel that is 0.07 in. (0.18 cm) thick and has an inner dimension of 

5.807 in. (14.75 cm.) A nominal generic 10B neutron absorber material was modeled having of a 

thickness of 0.09 in. (0.203 cm) and a nominal areal density of 0.021 g 10B/cm2

. The 10B areal density 

was varied from 100 percent to 10 percent while maintaining a constant thickness, and thermal neutron 

counts were tallied for the four BF3 detectors. The BF3 detectors were represented as 96 percent enriched 

in 10B, and the 252Cf source was represented at strength of 1 mCi. For all transmission ratio values, the 

attenuated region count rates correspond to a scan where the neutron absorber panel at a given areal 

density is present, and all unattenuated region count rates correspond to a scan where the absorber panel 

was represented as water maintaining the same detector-to-source orientation. The illustrative calibration 

plots are shown in Figure A.2. 
A-3 

Figure A.1. Cutaway view of representative Region II BWR storage rack model. 

neutron 

absorber 

panels

steel 

cell 

walls 
A-4 

Figure A.2. Areal density calibration curve for optimum source and detector head orientation 

positioning. 

Note: T = ratio of attenuated to unattenuated neutron counts 

Potential Uncertainty Due to Geometry Changes 

Three types of geometric misalignment can affect neutron transmission test results: tilt, twist, and offset 

(see descriptions in Reference 8 and in Section 5.5.1). Each misalignment condition results in changes in 

the distance between the detectors and the source and has the potential to introduce water between the 

detector head and the rack wall being evaluated. To evaluate the relative magnitude of these effects, 

SCALE models were developed to simulate the effects of twist and offset misalignment. 

Twist misalignment is when the probes are twisted instead of flush against the panel surface. Although 

different variants of twist misalignment can occur such as the source probe being twisted, the detector 

probe being twisted, or both probes being twisted, the SCALE models represented only the detector probe 

being twisted 1 ̊, 2 ̊, and 3 ̊. An example of twist misalignment is shown in Figure A.3. 

Offset misalignment can occur when the source and detector head are shifted. Spacer shims can be used to 

minimize the potential for this type of offset when the rack cell is significantly larger than the probe 

heads; however, there is still a clearance space that the heads could shift into. The offset represented in 

the SCALE model was 0.66-cm probe center-to-center distance, which represented the maximum offset 

y = 0.0007e-2.226x

R2 = 0.9918 y = 8.58E-04e-1.79x

R2 = 9.96E-01

y = 8.58E-04e-1.79x

R2 = 9.97E-01

y = 7.11E-04e-2.21x

R2 = 9.93E-01

0.00E+00

5.00E-03

1.00E-02

1.50E-02

2.00E-02

2.50E-02

-2 -1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0

Areal Density (10B g/cm2)

ln (T)

Surrogate Storage Rack

Det 1

Det 2

Det 3

Det 4
A-5 

geometrically allowable for the representative storage rack configuration. An example of offset 

misalignment is shown in Figure A.5. 

Figure A.3. Source and detector head positioning with 3° twist misalignment for detector head. 

Figure A.4. Source and detector head positioning with a 0.66-cm probe center-to-center offset 

misalignment. 

source 

detectors 

1 

2

3

4 

1 

2

3

4 

detectors source 
A-6 

The effects of twist misalignment can be observed in Table A-1 and Figure A.5 for 1°, 2°, and 3° twist 

misalignments, and the effects of offset misalignment are presented in Table A-2 and illustrated in Figure 

A.6. The percent change from optimum is the relative difference between the misaligned counting 

geometry results and the optimum orientation counting geometry results. BADGER areal density scan 

results are typically reported as an average of the four detectors, therefore the four detector average 

results are presented as well. The results show how sensitive the measurements are to very small changes 

in the distance between the source and detectors. Note that the differences reported here are based on a 

calibration curve for the same identical panel. BADGER test implementation incorporates the 

transmission data normalized to a reference panel and a slope from a separate calibration curve, 

exacerbating the uncertainty. 

Table A-1. Relative change in areal density due to twist misalignment 

Rotation Areal density 

(g 10B/cm2

) 

Detector 

(% change from optimum) 

Detector average

1 2 3 4 

1° 0.0212 22% 27% 30% 37% 29% 

 0.0148 9% 12% 20% 29% 18% 

 0.0085 -1% 13% 19% 25% 14% 

2° 0.0212 23% 36% 40% 51% 38% 

 0.0148 16% 25% 31% 42% 28% 

 0.0085 11% 23% 24% 35% 23% 

3° 0.0212 23% 39% 50% 57% 42% 

 0.0148 9% 30% 44% 51% 34% 

 0.0085 16% 26% 32% 44% 29% 

Figure A.5. Change in recorded areal density due to twist misalignment. 

0.00E+00

5.00E-03

1.00E-02

1.50E-02

2.00E-02

2.50E-02

1234

Areal Density (g10B/cm2)

Detector

Nominal Areal Density

1 degree twist

2 degree twist

3 degree twist
A-7 

Table A-2. Relative change in areal density due 

to offset misalignment

Areal density 

(g 10B/cm2

) 

Detector 

(% change from optimum) Detector average 

1 2 3 4 

0.0212 (100%) 13% 5% -6% -30% -5%

0.0148 (70%) -1% -13% -17% -44% -19%

0.0085 (40%) -9% -10% -16% -38% -18%

Figure A.6. Change in recorded areal density due to offset misalignment. 

The results of the twist misalignment cases indicate that even though the detectors are moving away from 

the source which would effectively reduce the detector count rate in a vacuum, the addition of water 

between the detector head and the panel allows neutrons that were not absorbed in the neutron absorber to 

become more thermalized so that they can register in the detectors. This effect is combined with the 

decrease in unattenuated count rate (the denominator in the transmission ratio) with increasing distance 

between the source and detectors. This results in a shift of the equivalent calibration curve to the right in 

this example, indicating that all results are at lower areal densities. The curve shift would be to the left if 

the misalignment first occurred during development of the initial calibration curve (i.e., results would 

show higher areal densities than are actually present). The effect of twist misalignment is more 

pronounced at higher areal densities than at lower areal densities owing to the steepness of the slope, as 

illustrated in Figure A.2. 

0.00E+00

5.00E-03

1.00E-02

1.50E-02

2.00E-02

2.50E-02

3.00E-02

1234

Areal Density (g 10B/cm2)

Detector

100% AD

70% AD

40% AD

100% AD

70% AD

40% AD
A-8 

The effects of offset misalignment exhibit the competing effects of neutrons that did not traverse through 

the neutron absorber panel for the edge detector combined with changes in distance from the source. The 

negative values shown in Table A-2 indicate where a nonconservative areal density change is being 

interpreted as an increase in relation to the nominal calibration curve. The amount of possible offset will 

be dependent upon the rack cell size, and the maximum uncertainty can be determined during initial 

calibration by taking measurements of the reference panel while maximizing the allowable offset. 

Another method to detect offest could be careful observation of the unattenuated region count data, which 

would rely on keen observation by the operator and/or analyst. 

A.1. REFERENCE 

A.1. SCALE: A Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design, 

ORNL/TM-2005/39, Version 6.1, Oak Ridge National Laboratory, Oak Ridge, Tennessee, June 

2011. Available from Radiation Safety Information Computational Center at Oak Ridge National 

Laboratory as CCC-785. 
B-1 

APPENDIX B

MAVRIC MODEL RESULTS 
B-2 

This appendix lists the SCALE MAVRIC model count rate results for each detector that were modeled in this report. optimum orientation configuration results, Table B-2 presents the twist misalignment results, and Table B-3 presents results. Tally responses are in units of per cm3 per second. 

Table B-1. MAVRIC-generated optimum orientation configuration results 

Panel areal 

density 

(g 10B/cm2) 

Detector 

1 2 3 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

Ta

Resp

0.0212 13.664 0.018 13.606 0.017 13.622 0.017 130.0191 14.202 0.017 14.127 0.017 14.385 0.017 130.0169 14.716 0.017 15.403 0.016 15.227 0.016 140.0148 15.349 0.016 15.919 0.016 16.496 0.016 140.0127 15.886 0.016 17.009 0.015 17.117 0.015 150.0106 17.120 0.015 19.414 0.014 19.372 0.014 170.0085 19.406 0.015 21.375 0.013 22.083 0.013 190.0064 22.821 0.013 26.288 0.012 26.949 0.012 220.0042 27.934 0.012 33.549 0.011 33.729 0.011 260.0021 36.869 0.011 47.329 0.009 47.630 0.009 36

unattenuated region 59.920 0.009 79.154 0.008 80.154 0.007 60
B-3 

Table B-2. MAVRIC-generated twist misalignment configuration results 

Rotation 

Panel areal 

density 

(g 10B/cm2) 

Detector 

1 2 3 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

R

1 ̊ 0.0212 14.698 0.017 15.389 0.016 15.345 0.016 1 ̊ 0.0148 16.152 0.016 16.909 0.016 17.338 0.015 1 ̊ 0.0085 19.768 0.014 23.217 0.013 23.541 0.013 21 ̊ unattenuated region 59.908 0.009 77.118 0.008 75.300 0.008 2 ̊ 0.0212 14.840 0.017 16.269 0.017 16.225 0.016 2 ̊ 0.0148 16.715 0.016 18.104 0.016 18.211 0.016 2 ̊ 0.0085 20.892 0.014 24.526 0.014 23.645 0.013 22 ̊ unattenuated region 59.865 0.009 75.962 0.008 72.798 0.008 3 ̊ 0.0212 14.918 0.017 16.478 0.016 17.111 0.016 3 ̊ 0.0148 16.264 0.016 18.593 0.015 19.655 0.016 3 ̊ 0.0085 21.628 0.014 24.722 0.013 24.093 0.014 23 ̊ unattenuated region 60.341 0.008 75.087 0.008 69.860 0.008 4
B-4 

Table B-3. MAVRIC generated offset misalignment configuration results 

Panel areal 

density 

(g 10B/cm2) 

Detector 

1 2 3 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

Tally 

Response 

Relative 

uncertainty 

Ta

Resp

0.0212 13.514 0.017 13.834 0.018 13.952 0.017 130.0148 14.895 0.014 15.405 0.013 16.126 0.013 140.0085 18.567 0.016 21.496 0.016 22.141 0.016 19

unattenuated region 58.831 0.009 82.173 0.007 86.743 0.007 69
C-1 

APPENDIX C

EXAMPLE MAVRIC CODE INPUT 

 
C-2 

'=============================================================================== 

' Basic MAVRIC Sequence items: title and SCALE Library 

'=============================================================================== 

=mavric 

Example for 10-B(n,alpha)3-Li reaction rate calculation 

v7-200n47g 

'------------------------------------------------------------------------------- 

' Composition Block - standard SCALE input 

'------------------------------------------------------------------------------- 

read composition 

 paraffin 1 1 293 end 

 polyethylene 2 1 293 end 

 wtpttype304ss 3 7.9 5 

 14000 1 

 24304 20 

 25000 2 

 26304 66.5 

 28304 10.5 

 1 293 end 

 b-10 4 0 1.05E-6 300 end 

 b-11 4 0 4.38E-8 300 end 

 f 4 0 3.28E-6 300 end 

 h2o 5 1 300 end 

 cf-252 6 1 300 end 

'neutron absorber panel 

 wtptalb4c 7 2.677 4 

 13027 75 

 5010 3.894 

 5011 15.672 

 6000 5.434 

 1 300 end 

'detector head neutron shield 

 wtptalb4c 8 2.677 4 

 13027 75 

 5010 3.894 

 5011 15.672 

 6000 5.434 

 1 300 end 

 al 9 1 300 end 

 h2o 10 1 300 end 

'test panel in rack 

 wtptalb4c 11 2.677 4 

 13027 75 

 5010 3.894 

 5011 15.672 

 6000 5.434 

 1 300 end 

end composition 

'------------------------------------------------------------------------------- 

' Geometry Block - SCALE standard geometry package (SGGP) 

'------------------------------------------------------------------------------- 

read geometry 

 global unit 1 

 com="global unit 1" 

'east cell description 

 cuboid 1 23.274 7.758 7.758 -7.758 40 -40 

 cuboid 2 23.071 7.961 7.555 -7.555 40 -40 

 cuboid 3 22.891 8.141 7.375 -7.375 40 -40 

 cuboid 4 23.274 23.071 5.82 -5.82 40 -40 

 cuboid 5 7.961 7.758 5.82 -5.82 40 -40 
C-3 

 cuboid 6 21.336 9.696 7.758 7.555 40 -40 

 cuboid 7 21.336 9.696 -7.555 -7.758 40 -40 

'west cell description 

 cuboid 11 -7.758 -23.274 7.758 -7.758 40 -40 

 cuboid 12 -7.961 -23.071 7.555 -7.555 40 -40 

 cuboid 13 -8.141 -22.891 7.375 -7.375 40 -40 

 cuboid 14 -7.758 -7.961 5.82 -5.82 40 -40 

 cuboid 15 -23.071 -23.274 5.82 -5.82 40 -40 

 cuboid 16 -9.696 -21.336 7.758 7.555 40 -40 

 cuboid 17 -9.696 -21.336 -7.555 -7.758 40 -40 

 

'north cell description 

 cuboid 21 7.758 -7.758 23.274 7.758 40 -40 

 cuboid 22 7.555 -7.555 23.071 7.961 40 -40 

 cuboid 23 7.375 -7.375 22.891 8.141 40 -40 

 cuboid 24 7.758 7.555 21.336 9.696 40 -40 

 cuboid 25 -7.555 -7.758 21.336 9.696 40 -40 

 cuboid 26 5.82 -5.82 23.274 23.071 40 -40 

 cuboid 27 5.82 -5.82 7.961 7.758 40 -40 

'south cell description 

 cuboid 31 7.758 -7.758 -7.758 -23.274 40 -40 

 cuboid 32 7.555 -7.555 -7.961 -23.071 40 -40 

 cuboid 33 7.375 -7.375 -8.141 -22.891 40 -40 

 cuboid 34 7.758 7.555 -9.696 -21.336 40 -40 

 cuboid 35 -7.555 -7.758 -9.696 -21.336 40 -40 

 cuboid 36 5.82 -5.82 -7.758 -7.961 40 -40 

 cuboid 37 5.82 -5.82 -23.071 -23.274 40 -40 

 cuboid 99 60 -60 60 -60 70 -70 

 hole 4 origin x=-15.4435 y=0 z=0 

 hole 2 origin x=-0.4555 y=0 z=0 

 

 media 5 1 1 -2 -4 -5 -6 -7 

 media 7 1 4 

 media 7 1 5 

 media 7 1 6 

 media 7 1 7 

 media 3 1 2 -3 

 media 5 1 3 

 

 media 5 1 11 -12 -14 -15 -16 -17 

 media 11 1 14 

 media 7 1 15 

 media 7 1 16 

 media 7 1 17 

 media 3 1 12 -13 

 media 5 1 13 

 media 5 1 21 -22 -24 -25 -26 -27 

 media 7 1 24 

 media 7 1 25 

 media 7 1 26 

 media 7 1 27 

 media 3 1 22 -23 

 media 5 1 23 

 media 5 1 31 -32 -34 -35 -36 -37 

 media 7 1 34 

 media 7 1 35 

 media 7 1 36 

 media 7 1 37 
C-4 

 media 3 1 32 -33 

 media 5 1 33 

 

 media 10 1 99 -1 -11 -21 -31 

 boundary 99 

 

 unit 2 

 com="unit 2" 

 cuboid 3 7.3025 -7.3025 7.3025 -7.3025 7.3025 -7.3025 

 cuboid 4 6.1913 -6.1913 6.1913 -6.1913 6.1913 -6.1913 

 cuboid 5 -3.6313 -6.1913 6.1913 -6.1913 6.1913 -6.1913 

 cuboid 6 -3.6513 -6.1913 6.1713 -6.1713 6.1913 -6.1913 

 

 cylinder 31 0.635 2.54 -2.54 origin x=-4.9213 y=4.6434 z=0 

 cylinder 32 0.635 2.54 -2.54 origin x=-4.9213 y=1.5478 z=0 

 cylinder 33 0.635 2.54 -2.54 origin x=-4.9213 y=-1.5478 z=0 

 cylinder 34 0.635 2.54 -2.54 origin x=-4.9213 y=-4.6434 z=0 

 

 media 4 1 31 vol=6.4352 

 media 4 1 32 vol=6.4352 

 media 4 1 33 vol=6.4352 

 media 4 1 34 vol=6.4352 

 

 media 9 1 3 -4 

 media 5 1 4 -5 

 media 8 1 5 -6 

 media 9 1 6 -31 -32 -33 -34 

 boundary 3 

 

 unit 4 

 com="unit 4" 

 cuboid 3 7.3025 -7.3025 7.3025 -7.3025 7.3025 -7.3025 

 cuboid 4 6.1913 -6.1913 6.1913 -6.1913 6.1913 -6.1913 

 hole 5 

 media 9 1 3 -4 

 media 5 1 4 

 boundary 3 

 

 unit 5 

 com="unit 5" 

 sphere 1 0.5 

 media 6 1 1 

 boundary 1 

end geometry 

'------------------------------------------------------------------------------- 

' Definitions Block 

'------------------------------------------------------------------------------- 

read definitions 

 response 5 

 title="the 10-B(n,alpha)3-Li macroscopic cross section" 

 mat=4 ZAID=5010 MT=107 macro 

 end response 

 distribution 1 

 title="Cf-252 neutrons, Watt spectrum a=1.025 MeV and b=2.926/MeV" 

 special="wattSpectrum" 

 parameters 1.025 2.926 end 

 end distribution 

end definitions 

'------------------------------------------------------------------------------- 

' Sources Block 
C-5 

'------------------------------------------------------------------------------- 

read sources 

 src 1 

 title="Cf-252 neutrons, Watt fission spectrum model, 1mCi" 

 strength=37.0e6 

 sphere 0.5 origin x=-15.4435 y=0.0 z=0.0 

 neutrons 

 eDistributionID=1 

 end src 

end sources 

'------------------------------------------------------------------------------- 

' Tallies Block 

'------------------------------------------------------------------------------- 

read tallies 

 regionTally 1 

 unit=2 region=1 

 responseIDs 5 end 

 end regionTally 

 regionTally 2 

 unit=2 region=2 

 responseIDs 5 end 

 end regionTally 

 regionTally 3 

 unit=2 region=3 

 responseIDs 5 end 

 end regionTally 

 regionTally 4 

 unit=2 region=4 

 responseIDs 5 end 

 end regionTally 

end tallies 

'------------------------------------------------------------------------------- 

' Parameters Block 

'------------------------------------------------------------------------------- 

read parameters 

 randomSeed=00003ecd7b4e3e8b 

 perBatch=100000 batches=50 

 noFissions 

 noSecondaries 

end parameters 

end data 

end