Validation of BWR spent nuclear fuel isotopic predictions with applications to burnup credit

Validating boiling water reactor (BWR) spent nuclear fuel inventory calculations is challenging due to the complexity of BWR assembly designs, the lack of publicly available radiochemical assay measurements, and limited access to documentation on fuel design and operating conditions.

Nuclear Engineering and Design 345 (2019) 110–124 Contents lists available at ScienceDirect Nuclear Engineering and Design journal homepage: www.elsevier.com/locate/nucengdes Validation of BWR spent nuclear fuel isotopic predictions with applications to burnup credit☆ T ⁎ I.C Gauld , U Mertyurek Oak Ridge National Laboratory, P.O Box 2008, Oak Ridge, TN 37834, USA A R T I C LE I N FO A B S T R A C T Keywords: Boiling water reactor Radiochemical assay data Isotopic validation Burnup credit Validating boiling water reactor (BWR) spent nuclear fuel inventory calculations is challenging due to the complexity of BWR assembly designs, the lack of publicly available radiochemical assay measurements, and limited access to documentation on fuel design and operating conditions This study compiled and evaluated experimental data on measured nuclide concentrations in commercial spent fuel for 77 fuel samples that cover a wide range of modern assembly designs and operating conditions These data were used to validate predictions of the isotopic content using the SCALE Polaris lattice physics depletion code The isotopic bias and uncertainties derived from comparisons of calculated and measured nuclide concentrations are applied to estimate the combined effect on the effective neutron multiplication factor for a representative burnup credit spent nuclear fuel storage system The experimental data, validation results, model uncertainties, and uncertainty analysis results for a cask burnup credit application system are described Introduction Quantifying bias and uncertainty in the calculated nuclide compositions of spent nuclear fuel is essential for validating the codes and nuclear data used for many safety and licensing calculations This is most often accomplished by comparing calculated spent fuel nuclide contents directly with measurements obtained by nondestructive or destructive radiochemical assay (RCA) of spent fuel samples that are representative of the application model Isotopic measurement data have been widely used internationally by industry and research institutes to validate depletion capabilities, and they are used extensively by Oak Ridge National Laboratory (ORNL) to validate the SCALE code system (Rearden and Jessee, 2017) Previous SCALE validation studies using RCA data have focused mainly on pressurized water reactor (PWR) spent fuel More than 120 fuel samples from PWR spent fuel have been analyzed by ORNL in support of PWR burnup credit and other safety activities (Radulescu et al., 2014; Ilas et al., 2012) However, analysis of boiling water reactor (BWR) spent fuel (Hermann and DeHart, 1998; Wimmer, 2004; Mertyurek et al., 2010), has been more limited due to a lack of measurements of BWR spent fuel compositions for modern assembly designs with well-documented operating information The restricted availability of public sources of BWR spent fuel assay data for modern assembly designs and enrichments is due in part to the commercial proprietary nature of the newer assembly designs, enrichment configurations, and operating conditions in the reactor Publicly available spent fuel measurements previously considered for BWR isotopic validation in the United States have included early × (Barbero et al., 1979) and × (Guenther et al., 1991) BWR assemblies with relatively low enrichments and designs that lacked the heterogeneity of modern BWR assemblies Moreover, the coolant axial void conditions for these older assemblies were not reported Measurements of an × BWR assembly from the Fukushima Daini-2 reactor were reported by the Japan Atomic Energy Agency (JAEA) with coolant void information included (Nakahara et al., 2000); these data were also used in the earlier isotopic validation studies Measurements for newer BWR designs are largely available only through proprietary experimental programs Over the past decade there has been increased international recognition of the need for expanded, high quality, public sources of experimental data to validate spent fuel calculations In 2006, the Nuclear Science Committee of the Organisation for Economic ☆ This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to so, for US government purposes DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) ⁎ Corresponding author Tel.: +1-865-574-5257 E-mail address: gauldi@ornl.gov (I.C Gauld) https://doi.org/10.1016/j.nucengdes.2019.01.026 Received 12 November 2018; Received in revised form 24 January 2019; Accepted 25 January 2019 Available online 20 February 2019 0029-5493/ © 2019 The Authors Published by Elsevier B.V This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/) Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Cooperation and Development/Nuclear Energy Agency (OECD/NEA) established an Expert Group on Assay Data of Spent Nuclear Fuel (EGADSNF) to compile, document, and evaluate a comprehensive set of publicly available RCA data (OECD/NEA, 2019) and to make these data available through the OECD/NEA web-based Spent Fuel Isotopic Composition Database (SFCOMPO) This database is managed as an activity under the OECD/NEA Working Party on Nuclear Criticality Safety (WPNCS) The updated database, SFCOMPO 2.0 (Michel-Sendis et al., 2017), was released publicly in 2017, with contributions from many NEA member countries The database is intended to support engineering and safety analyses for nuclear fuel cycle applications and back-end nuclear facilities related to fuel handling, dry spent fuel storage installations, pool storage, fuel reprocessing facilities, and waste repositories New BWR measurements are included in SFCOMPO from recent publications, and extensive contributions from the Japan Nuclear Regulation Authority (NRA) are also included This paper describes a validation study of BWR isotopic predictions using the expanded experimental database of destructive RCA measurements and calculations performed with the Polaris lattice physics code (Jessee et al., 2014) in SCALE 6.2.2 (Rearden and Jessee, 2017) using Evaluated Nuclear Data File/B Version VII.1 (ENDF/B-VII.1) nuclear cross section and decay data (Chadwick et al., 2011) The concept of taking credit for the reduction in reactivity due to fuel burnup is commonly referred to as burnup credit The reduction in reactivity that occurs with burnup is due to the change in concentration (net reduction) of fissile nuclides and the production of actinide and fission-product neutron absorbers Interim Staff Guidance (Interim Staff Guidance, 2012) on the implementation of burnup credit for storage and transportation systems (ISG-8 rev 3) issued in 2012 by the US Nuclear Regulatory Commission (NRC) applies only to PWR fuel assemblies The studies described in the present work are motivated by the desire to develop an improved technical basis for BWR spent fuel criticality safety analyses using burnup credit The range of application applies to BWR fuel burnup beyond the region of peak reactivity that is associated with the use (depletion) of fuel containing gadolinium oxide (Gd2O3) or other integral neutron absorbers that are widely used in modern BWR assembly designs In addition to the public BWR data in the SFCOMPO database, this work applies measurements for a modern General Electric (GE) GE14 10 × 10 fuel assembly made under a proprietary experimental program coordinated by the Spanish fuel manufacturer ENUSA Industrias Avanzadas, S.A and the Spanish Nuclear Safety Council, Consejo de Seguridad Nuclear (CSN) (Conde et al., 2006) Data were also obtained for a SVEA-96 10 × 10 assembly from the proprietary MOX and UOX LWR Fuels Irradiated to High Burnup (MALIBU) experimental program coordinated by the Belgian Nuclear Research Center (SCK·CEN) (Boulanger et al., 2004) Additional data for a GE11 × assembly design were obtained from measurements made under the US Department of Energy Office of Civilian Radioactive Waste Management (OCRWM) Yucca Mountain project (Radulescu, 2003) These data provide an improved experimental basis for the evaluation of BWR isotopic uncertainties by including modern heterogeneous assembly designs, expanded isotopic measurements, and more complete reactor operating history information At this writing, some of these data are commercially protected but may be made available in the future through nondisclosure agreements to support licensing activities In this study, an application of BWR isotopic uncertainty analysis was applied to a nuclear criticality safety burnup credit model The uncertainty in keff due to biases and uncertainties in calculated nuclide concentrations is presented Criticality calculations were performed using the KENO V.a Monte Carlo neutron transport code and the 252energy group ENDF/B-VII.1 cross section library available in SCALE 6.2.2 Credit for fuel burnup was considered for the major actinides in spent fuel (Parks et al., 2000) with and without the addition of minor actinides and principal fission products (Table 1) Table Actinides and fission products considered in the burnup credit criticality analyses U† Pu† 101 Ru 149 Sm 234 240 † U† Pu† 103 Rh 150 Sm 235 241 U† Am† 133 Cs 152 Sm 236 238 242 241 U Pu† 109 Ag 151 Sm Pu† Mo 145 Nd 153 Eu 237 238 243 95 Np Am 143 Nd 151 Eu Pu† Tc 147 Sm 155 Gd 239 99 Major actinides Fig Polaris lattice physics calculation flow (Williams and Kim, 2012) Code and modelling descriptions 2.1 Lattice physics and depletion analyses Polaris is a new module introduced in SCALE 6.2 that provides twodimensional (2D) multigroup (MG) neutron transport lattice physics with pin-by-pin depletion capability for production calculations of light water reactor (LWR) fuel assembly designs A detailed description of the methods and calculational approach of Polaris is provided by Jessee et al (2014) The calculational flow of the Polaris code is shown in Fig Polaris was developed as an efficient transport and depletion code specifically for LWR analyses to supplement the general-purpose TRITON depletion capability (DeHart and Bowman, 2011) in SCALE, which uses one-dimensional (1D, XSDRN), 2D (NEWT), or three-dimensional (3D) Monte Carlo (KENO) neutron transport solutions For the neutron transport calculation, Polaris employs the method of characteristics (MOC), which solves the characteristic transport equation over a set of equally spaced particle tracks across the lattice geometry Polaris also provides an easy-to-use input format allowing users to set up lattice models with a minimal amount of input as compared to TRITON input requirements An efficient embedded self-shielding method (ESSM) is used in Polaris for resonance self-shielding of all fuel rods in an assembly (Williams and Kim, 2012) ESSM is similar to the subgroup method, in which the effects of neighboring fuel pins, guide tubes, water rods, and assembly structures are accounted for in the self-shielding calculations ESSM neglects resonance interference between resonance-absorbing nuclides in the same material Although Bondarenko iteration option is 111 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Table Summary of BWR spent fuel samples Reactor and Unit Country Assembly Design Number of Samples Enrichments (wt % Dodewaard Forsmark Forsmark 3a Fukushima Daini Fukushima Daini Fukushima Daini Leibstadt 3b Limerick 1c Belgium Sweden Sweden Japan Japan Japan Switzerland United States 6×6 10 × 10 (SVEA-96) 10 × 10 (GE14) 9×9 – 8×8 – 8×8 – 10 × 10 (SVEA-96) × (GE11) 1 13 25 18 4.94 3.97 3.95 2.1, 4.9, 3.0 (Gd) 3.4, 4.5, 3.4 (Gd) 3.9, 3.4 (Gd) 3.9 3.95, 3.6 (Gd) a b c 235 U) Burnup (GWd/MTU) 55 61 38–50 35–68 9–59 7–44 56–63 37–65 Spanish Nuclear Safety Council (CSN), proprietary data MALIBU International Program, proprietary data US DOE Yucca Mountain Project, proprietary data KENO V.a criticality calculations of the application model were performed using the 252-group ENDF/B-VII.1 neutron transport cross section library in SCALE in order to evaluate differences in isotope concentrations accurately available to treat resonance interference in Polaris, its effect is minimal for UO2 depletion calculations Cross section self-shielding is performed automatically to account for changes in the coolant void fraction and other operating conditions during the depletion analysis In previous depletion studies of BWR fuel that were performed using TRITON, Dancoff factors used for resonance cross section corrections for nonuniform lattices had to be calculated externally, usually with the MCDANCOFF code in SCALE or an equivalent code, and then applied manually as input to the model (Mertyurek et al., 2010) When the Dancoff factors changed during irradiation due to variations in the moderator void and burnup, updating the factors required halting the calculation, saving the intermediate nuclide concentrations, entering new Dancoff factors, and restarting the case This procedure is performed internally in Polaris Polaris is coupled to the ORIGEN code (Gauld et al., 2011) to solve the time-dependent transmutation equations and calculate nuclide concentrations, activities, and radiation source terms for the many isotopes simultaneously generated or depleted by neutron transmutation, fission, and radioactive decay Polaris has been validated for reactor physics lattice calculations Comparisons of Polaris and TRITON/CE KENO results show acceptable accuracy for lattice physics calculations with less than 200 pcm difference in kinf (Mertyurek et al., 2018) The present study represents the first application of Polaris for extensive BWR isotopic validation Experimental assay data Measured BWR nuclide compositions were obtained from destructive RCA experiments of spent fuel rods from assemblies irradiated in eight different reactors operated in five countries These assemblies include × 6, × 8, × 9, and 10 × 10 lattice designs Many datasets were available from SFCOMPO 2.0 (Michel-Sendis et al., 2017) All primary experimental reports on each dataset are maintained and made available as part of the database Measurements from the Dodewaard, Forsmark 3, Fukushima Daini 1, and Fukushima Daini reactors were used in this study since they include relatively complete design and operating history data More than 80% of the samples analyzed were from Fukushima Daini Units and operated in Japan Several experimental datasets analyzed in previous studies (Hermann and DeHart, 1998; Wimmer, 2004) were not used in the current study due to insufficient documentation on the reactors’ operating conditions, most notably the availability of axial void fractions for the samples Previous studies used semi empirical correlations of assembly power and core coolant inlet temperature to estimate the missing local void fraction data for measured assemblies In this study, only experimental datasets with reported axial void fractions were considered Additional data used in this study were obtained from commercial proprietary programs that measured fuel samples from the Forsmark 3, Leibstadt 3, and Limerick reactors Descriptive data included in this paper are therefore limited to information available from public sources Additional information required for modeling and simulation of these fuel assemblies is only available through nondisclosure agreements The measured data used herein are summarized in Table A total of 77 samples were analyzed Measurements of all the major actinide isotopes (Table 1) are available for most samples Minor actinide and fission product measurements are available for many of the samples A brief description of each experimental dataset used in the present study is provided in the following sections More detailed information is available in the primary experimental reports cited in this paper 2.2 Nuclear data libraries Neutron transport calculations in Polaris were performed using the 56-group ENDF/B-VII.1 cross section library for all results presented in this report Fifty-six group cross section library is a subset of 252-group library and is optimized for fast lattice physics calculations with less than 150 pcm bias in kinf for UO2 fuel Following each transport calculation performed by Polaris, cross sections are collapsed in energy using the neutron spectrum in each fuel rod and applied directly to the ORIGEN calculation to determine reaction rates and the nuclide transmutation inventories ENDF/B-VII.1 (Chadwick et al., 2011) provides cross sections for 388 individual isotopes Cross sections for 386 isotopes not available in ENDF/B-VII.1 are taken from a special-purpose MG activation library based on JEFF-3.1/ A (Sublet et al., 2003) and are collapsed using the same procedures Due to their negligible self-shielding and impact on transport calculations, cross sections obtained from the JEFF-3.1/A library are not processed through the ESSM module and are applied as unshielded (infinitely dilute) cross sections All decay data used by ORIGEN are adopted from ENDF/B-VII.1 Independent fission product yields are developed from England and Rider (1994), as included in ENDF/B-VII.0 The independent fission yields used by ORIGEN have been adjusted to account for changes in the decay data to provide greater consistency with the cumulative fission yields in the England and Rider evaluation (Pigni et al., 2015) 3.1 Dodewaard (6 × 6) Dodewaard was a BWR nuclear power plant that operated in the Netherlands until 1997 Destructive RCA measurements were performed on fuel samples as part of the Actinide Research in a Nuclear Element (ARIANE) international project (Primm, 2002) Experimental data from ARIANE were released publicly to the OECD/NEA, and the measurement data and experimental reports are available through the 112 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek dependent operating data were applied in the Polaris model An effective fuel temperature was calculated from the fuel center and surface temperatures using Rowlands’s formulation (Rowlands, 1964) The sample burnup was determined by matching the 148Nd concentration predicted by Polaris with the measurement data, which were estimated by the laboratories to have an accuracy of better than 1% (95% confidence) 3.2 Forsmark SVEA-100 (10 × 10) Measurements of fuel samples from SVEA-100 10 × 10 fuel assembly 14595, irradiated in the Forsmark Unit reactor located in Sweden, were performed at the Studsvik Nuclear Laboratory Sample F3F6 from the central part of the UO2 rod located at position F6 of assembly 14,595 was dissolved at Studsvik and measurements performed in 2003 and 2006 Aliquots of the fuel solution were also shipped to two other laboratories in 1996, Harwell in the United Kingdom and Dimitrovgrad in Russia, for independent radiochemical determination of the isotopic composition and burnup analysis These measurements and the experimental report were published in 2008 by Zwicky (2008) and are available through the SFCOMPO database, and computational analyses of this sample were reported by Hannstein and Sommer (2017) Sample F3F6 was obtained at an axial position 2004 mm from the bottom of the fuel rod and experienced an average void fraction of 58% The fuel sample characteristics are listed in Table The measurements performed at Studsvik in 2006 were used in this study The sample burnup was estimated by Studsvik based on the measurements using weighted burnup values based on measurements of neodymium, 235U, and 239Pu isotopes The layout of the Forsmark-3 assembly 14,595 is shown in Fig 3, with the location of the measured rod F6 at the inner corner of the assembly subchannel and the subchannel structure (water cross) shown The assembly used 10 different fuel rod enrichments, and five rods had a Gd2O3 content of 3.15 wt% Detailed time-dependent void fractions, fuel temperature, and specific power for the measured sample are provided in the report by Zwicky (2008) Fig Polaris model of Dodewaard × assembly SFCOMPO database The Dodewaard UO2 sample, DU1, had an initial 235U enrichment of 4.94% and was irradiated for five cycles to ∼55 GWd/MTU in fuel assembly Y013 The assembly was an early BWR × lattice design containing one water rod and five gadolinium oxide (Gd2O3) rods The assembly layout is shown in the Polaris model in Fig The basic fuel sample characteristics are listed in Table The other fuel rods in the assembly were standard, full-length UO2 rods with variable enrichments (3.2, 2.6, and 1.8 wt%) except for two experimental rods located in positions D5 and E4 (see Fig 2) that contained mixed oxide (MOX) with 6.43 wt% plutonium content The MOX rods were positioned away from the measured sample Two gadolinium rods with 2.7 wt% Gd2O3 content in fuel and 3.2% enriched in 235 U were adjacent to the measured rod Assembly Y013 is not highly representative of modern designs, and it contained a segmented test rod from which sample DU1 was obtained However, detailed design and operating history information was available from the operator at the sample axial location, and extensive nuclide measurements were reported Applicability of the DU1 sample for validation has been independently evaluated (Ortego and Rodríguez, 2013), and it was concluded that these data are suitable for validating isotopic depletion codes Independent measurements of the DU1 sample were performed at laboratories of the Belgian Nuclear Research Center, Studiecentrum voor Kernenergie (SCK·CEN), in 1996, and at the Paul Scherrer Institute (PSI) in Switzerland in 1999 (Primm, 2002) Measurement data are available for all 28 burnup credit isotopes listed in Table In the current study, calculated nuclide concentrations were compared to both sets of measurements to provide an estimate of the impact of measurement uncertainties Detailed core follow data for the measured sample are included in the ARIANE report Time-dependent void fraction, burnup, center, and surface fuel temperatures are provided for all five cycles These time- 3.3 Forsmark GE14 (10 × 10) Under a proprietary Spanish experimental program (Conde et al., 2006) coordinated by the Spanish fuel vendor ENUSA, isotopic measurements were made on a modern GE14 10 × 10 assembly from the Forsmark Unit reactor operated in Sweden Fuel samples from rod J8 from assembly GN592 were measured at Studsvik Nuclear Laboratory (Zwicky et al., 2010) A total of eight fuel samples from the fuel rod were measured over the rod’s length to provide data for burnup and void variations Two pairs of samples—samples and 2, and samples and 7—from adjacent axial positions of the rod, were selected to verify measurement repeatability and uncertainty The measurements provided isotopic data at six unique axial positions and included more than 60 isotopes; this isotope set includes most of the burnup credit isotopes listed in Table All samples from rod J8 were from the enriched zone of the rod with an initial enrichment of 3.95 wt% 235U The fuel rod attained an estimated rod average burnup of 41 GWd/MTU and a peak burnup of ∼56 GWd/MTU Table summarizes sample identification names, the elevation of each sample, and the void at the sample locations from the reactor Table Summary of Dodewaard × assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm) Avg Void (%) Enrichment (wt % Y013 B2 DU1 UO2 1111 50 4.941 113 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 55.5 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Table Summary of Forsmark Unit SVEA-100 10 × 10 assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm) Avg Void (%) Enrichment (wt % 14595 F6 F3F6 UO2 2004 58 3.97 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 55.8 Fig Polaris model of Forsmark Unit SVEA-100 assembly Fig Polaris model of Forsmark Unit GE14 10 × 10 assembly operating history data Sample elevations were measured from the lower end plug of the fuel rod The distance from the lower end plug to the start of the active fuel region is ∼40 mm The layout of GE14 assembly GN592 is shown in Fig This assembly has 92 fuel rods, including 12 part-length rods; nine of the rods contain Gd2O3 in fuel Seven different uranium enrichments are used in the assembly Detailed, time-dependent reactor operating data, including void fraction, fuel temperature, and power for the measured samples, are documented in reference reports prepared by Vattenfall in Sweden (Lindström, 2011) irradiation This assembly design is similar to the ATRIUM-9 design Measurements for isotopes of uranium, plutonium, and neodymium were reported by Yamamoto and Kanayama (2008), Yamamoto (2012) for eight samples selected from five different fuel rods of the two assemblies Another five samples from the same rods were later reported on by Suzuki et al (2013), including measurements of additional fission products The supplementary design and operating information necessary to model the × – assemblies were provided by Yamamoto (2014) through the OECD/NEA-coordinated activity on spent fuel assay data These data and reports are currently available through the SFCOMPO database The supplemental data included the fuel rod enrichment layout, time-dependent void fractions, and accumulated burnup for the assemblies at the axial locations (nodes) of all measured samples The configuration of assemblies 2F1ZN2 and 2F1ZN3 is shown in Fig 5; the measured rod locations C2, C3, and A9 are highlighted The assemblies used five different 235U enrichments and contain 12 Gd2O3 fuel rods, as indicated by the different colored rods in the figure The measurements include both UO2 and UO2-Gd2O3 type fuel rods, with initial enrichments of 2.1, 3.0, and 4.9 wt% 235U The C2 fuel rods (see Fig 5) contained Gd2O3 with a content of wt% in the fuel The sample 3.4 Fukushima Daini (9 × – 9) As part of a validation study of burnup calculations of BWR cores conducted by Japan’s NRA (formerly the Japan Nuclear Energy Safety [JNES] organization), physics and depletion analyses were performed using post-irradiation measurements of burnup and isotopic inventories of eight samples taken from two × – BWR lead test fuel assemblies irradiated in the Fukushima Daini Unit reactor (2F1) Assemblies 2F1ZN2 and 2F1ZN3 were discharged after three and five cycles of Table Summary of Forsmark Unit GE14 10 × 10 assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm) Avg Void (%) Enrichment (wt % GN592 J8 ENUSA-1 ENUSA-2 ENUSA-3 ENUSA-4 ENUSA-5 ENUSA-6 ENUSA-7 ENUSA-8 UO2 UO2 UO2 UO2 UO2 UO2 UO2 UO2 1847 1858 718 2508 3282 403 707 3389 51 51 13 61 67 2.2 13 67 3.95 3.95 3.95 3.95 3.95 3.95 3.95 3.95 114 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 0 0 0 0 50.4 50.7 49.0 51.1 43.6 43.5 49.0 38.3 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek % 235U and contained 4.5 wt% Gd2O3, whereas the upper section was enriched to 3.40 wt% 235U and contained 3.0 wt% Gd2O3 Measurements were reported for 18 different samples obtained from different axial positions of the two rods Three samples were selected from the natural uranium blanket regions near the ends of rods The sample characteristics are provided in Table The sample axial locations in the fuel rods were measured from the bottom of the active fuel length The burnup values were estimated from the measured 148Nd content in the fuel samples Measurements were performed at the JAEA laboratories The configuration of assembly 2F2DN23 is shown in Fig The × – assembly is similar to the GE7 design Time-dependent void data were not available for this assembly The average void fractions are those provided by TEPCO and are standard values as written in the Application for Permission for the Installation of a Nuclear Reactor (Nakahara et al., 2002) The impact of using average void data compared to detailed void data is assessed in Section 5.3 of this paper 3.6 Fukushima Daini GE9 (8 × – 4) Isotopic measurements of four BWR × – lead test assemblies, irradiated in Unit of the Fukushima Daini Power Station (2F2), were report by the Japan NRA (Yamamoto, 2012; Yamamoto and Yamamoto, 2008) The assemblies, identified as 2F2D1, 2F2D2, 2F2D3, and 2F2D8, were discharged after one, two, three, and five cycles of irradiation, respectively, providing a wide range of sample burnups The measurements, design data, and reference reports are included in the SFCOMPO database The configuration of the assembly is shown in Fig All assemblies have the same layout and enrichment zoning and used five different 235 U enrichments and eight UO2-Gd2O3 rods with Gd2O3 contents of 3.0 and 4.5 wt% in the fuel Measurements for each assembly include both UO2 and UO2-Gd2O3 type fuel rods The sample characteristics are given in Table Time-dependent void distributions for the × – assemblies were not reported However, the node average values of the channel void fractions of the assemblies were available from the plant operator for all axial nodes that included the measured fuel samples (Yamamoto and Yamamoto, 2008) Measurements were made at the laboratories of the Nippon Nuclear Fuel Development (NFD) Company, including data for isotopes of U, Pu, 148 Nd, 241Am, and Cm The sample burnups were estimated by the laboratory based on the 148Nd method with the inventory data of uranium, plutonium The burnup values used in this study used the measured 148Nd content in each sample Fig Polaris model of the Fukushima Daini-1 × – assemblies burnup was estimated using the measured 148Nd concentration A summary of the measured sample characteristics is given in Table The axial elevations of each sample are relative to the bottom of the active region of the fuel rod 3.5 Fukushima Daini (8 × – 2) Under a burnup credit research project at the Japan Atomic Energy Research Institute (JAERI), supported by the Science and Technology Agency of Japan in cooperation with the utilities, experiments were performed on spent fuel assemblies to obtain criticality data for burnup credit Under this program, destructive and nondestructive measurements were made to determine the nuclide compositions of the fuel (Nakahara et al., 2000) Analyses of these data have been reported by Nakahara et al (2002) and Yamamoto and Yamamoto (2008) The measurements and the reference reports are compiled as part of the SFCOMPO database Measurements are reported for two fuel rods from lattice positions B2 and C2 of an × – assembly identified as 2F2DN23 This assembly was irradiated for three cycles in Unit of the Fukushima Daini Power Station (2F2) reactor, which is operated by Tokyo Electric Power Company (TEPCO) Rod C2 was a UO2-Gd2O3 rod with two axial enrichment zones The lower 2937 mm section was enriched to 3.40 wt 3.7 Leibstadt SVEA-96 (10 × 10) Measurements from the MALIBU international experimental Table Summary of Fukushima Daini-1 × – assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm) Avg Void (%) Enrichment (wt % 2F1ZN2 C2 GDB GDT UB UT UO2-Gd2O3 UO2-Gd2O3 UO2 UO2 757 2922 788 2922 18 74 18 74 UB UM UT GDB GDM GDT UB UM UT UO2 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2 UO2 UO2 788 1654 2844 804 1654 2875 788 1639 2844 18 38 60 18 38 60 11 38 60 C3 2F1ZN3 A9 C2 C3 115 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 3.0 3.0 4.9 4.9 5.0 5.0 0 35.6 29.0 46.5 38.9 2.1 2.1 2.1 3.0 3.0 3.0 4.9 4.9 4.9 0 5.0 5.0 5.0 0 61.2 68.0 55.7 55.6 57.7 46.8 68.3 68.4 58.0 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Table Summary of Fukushima Daini-1 × – assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm)a Avg Void (%) Enrichment (wt % 2F2DN23 B2 SF98-1 SF98-2 SF98-3 SF98-4 SF98-5 SF98-6 SF98-7 SF98-8 SF99-1 SF99-2 SF99-3 SF99-4 SF99-5 SF99-6 SF99-7 SF99-8 SF99-9 SF99-10 UO2 UO2 UO2 UO2 UO2 UO2 UO2 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2 39 167 423 692 1214 2050 2757 3397 134 286 502 686 1189 2061 2744 3388 3540 3676 0 11 32 54.5 68 73 1.4 5.8 10.8 27.7 54.7 66.5 71.7 72.9 74.3 0.71 3.91 3.91 3.91 3.91 3.91 3.91 3.91 0.71 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 0.71 C2 a 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 0 0 0 0 4.5 4.5 4.5 4.5 4.5 4.5 3.0 3.0 4.2 26.5 36.9 42.4 44.0 39.9 39.4 27.2 7.5 22.6 32.4 35.4 37.4 32.4 32.1 21.8 16.7 7.2 Measured from the bottom of the active fuel length Fig Polaris model of the Fukushima Daini-2 × – assemblies Fig Polaris model of the Fukushima Daini-2 × – assemblies program (Boulanger et al., 2004) were analyzed in this study MALIBU is a commercial proprietary program managed by SCK·CEN Independent measurements were performed at several radiochemical laboratories to serve as a measurement cross check and to assess and reduce uncertainties Isotopic measurements were made on BWR fuel samples from a SVEA-96 Optima 10 × 10 assembly from the Kernkraftwerk Leibstadt reactor in Switzerland (MALIBU Program, 2015) Three samples were taken at different axial positions of rod H6 of assembly AIA003 to assess different void conditions All samples had an initial enrichment of 3.90 wt% 235U Characteristics of the measured samples are given in Table The burnup values for samples KLU1 and KLU3 were determined using the 148Nd concentration; this burnup was in good agreement with burnup estimates based on other neodymium isotopes and 137Cs The KLU2 sample used 145+146Nd and 137Cs measurements to estimate the sample burnup, which was about 8% different from the burnup obtained using 148Nd The assembly layout is shown in Fig for the configuration of the dominant lattice (below the level of the part length rods) Detailed operating data, including time-dependent specific power, void conditions, and fuel temperatures, were provided by the Vattenfall Nuclear Fuel and Kernkraftwerk Leibstadt (MALIBU Program, 2010) All samples were measured at Studsvik Nuclear Laboratory in Sweden during 2010 The sample at the lowest elevation, KLU1, was selected as a cross check sample and was also analyzed at the laboratories of SCK·CEN in Belgium and the PSI in Switzerland Radiochemical analysis techniques were used to analyze more than 50 actinides and fission products 3.8 Limerick GE11 (9 × 9) Measurements of a spent fuel assembly from the Limerick Unit reactor were measured in laboratories at GE Vallecitos Nuclear Center These measurements have been analyzed in previous validation studies performed under the Yucca Mountain Project (YMP) in 2004 under the Office of Civilian Radioactive Waste Management (Radulescu, 2003) 116 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Table Summary of Fukushima Daini-2 × – assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm)a Avg Void (%) Enrichment (wt % 2F2D1 F6 TU101 TU102 TU103 TU104 TU105 TU106 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 UO2 3378 642 3343 2743 740 2689 64.0 12.9 64.0 60.2 17.3 59.8 TU201 TU202 TU203 TU204 TU205 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 3178 478 3178 2592 578 TU301 TU302 TU304 TU306 TU308 TU309 TU311 UO2 UO2 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 UO2-Gd2O3 TU501 TU502 TU503 TU505 TU506 TU510 TU511 UO2 UO2 UO2 UO2 UO2 UO2-Gd2O3 UO2-Gd2O3 B3 F6 2F2D2 F6 B3 2F2D3 H5 A4 B3 2F2D8 H5 A4 B3 a 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 4.5 4.5 3.4 3.4 3.4 4.5 0 4.5 4.5 4.5 14.0 18.2 10.0 9.4 12.3 16.1 63.1 7.0 63.1 58.5 10.4 4.5 4.5 3.4 3.4 3.4 0 4.5 4.5 4.5 29.1 32.9 24.5 23.5 22.8 2793 423 2856 447 3242 2780 543 60.6 5.2 61.0 6.0 63.5 60.5 9.1 3.4 3.4 3.4 3.4 3.4 3.4 3.4 0 0 4.5 4.5 4.5 34.6 31.4 37.8 32.3 30.2 34.8 33.5 3202 2453 803 2229 850 2952 670 63.2 58.0 20.6 54.9 23.0 62.2 14.0 3.4 3.4 3.4 3.4 3.4 3.4 3.4 0 0 4.5 4.5 53.2 58.9 55.6 59.1 57.5 53.1 48.1 Gd content (wt % Gd2O3) Burnup (GWd/MTU) 0 60.5 65.0 58.4 Measured from the bottom of the active fuel length Table Summary of Leibstadt SVEA-96 10 × 10 assembly fuel sample measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm)a Avg Void (%) Enrichment (wt % AIA003 H6 KLU1 KLU2 KLU3 UO2 UO2 UO2 588 1922 3302 8.4 51 70 3.90 3.90 3.90 a 235 U) Measured from the bottom of the active fuel length Measurements were performed for eight samples selected from a highburnup assembly YJ1433 (Reager, 2003) The reported measurement data include nuclide concentrations for 32 actinides and fission products The measured nuclides include isotopes of U, Pu, Nd, Gd, Sm, Eu, Am, Cm, Np, and Cs Assembly YJ1433 is a GE11 × design with two large water rods There are five different 235U enrichments for the UO2 rods, eight partlength rods, and nine rods containing Gd2O3 at wt% in the fuel The assembly configuration is shown in Fig The assembly was irradiated for three cycles Three different fuel rods were measured, including a full length UO2 rod from lattice location D9, a UO2-Gd2O3 rod from location D8, and a part-length UO2 rod from location H5 The characteristics of the measured samples are listed in Table 10 The burnup values assigned to these samples are based on values determined by GE Nuclear Energy (Reager, 2003) using uranium, plutonium, and neodymium isotope ratios However, for some samples, large deviations of up to 7% were observed between measured and calculated 148Nd content, a common burnup indicator Adjusting the burnup in the calculations to match the measured 148Nd content resulted in large deviations in other burnup indicator nuclides The inconsistencies in sample burnup have not been resolved The impact of uncertainties in the estimated sample burnup values is assessed in Section 5.3 of this paper The reported void fraction distribution with the Limerick data are not based on detailed core simulation codes but were instead developed by using time-dependent core average axial void fraction and detailed 3-D power profile, potentially introducing additional uncertainty in the Fig Polaris model of Leibstadt SVEA-96 10 × 10 assembly 117 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Fig Polaris model of Limerick-1 GE11 × assembly void fraction values The Limerick measurements were previously evaluated under the YMP project using depletion codes employing both 1D transport models (Radulescu, 2003) and 2D models (Mays, 2004) The detailed design information for the GE11 assembly and the operating history data for assembly YJ1433 are currently not public, but they may be made available in the future through nondisclosure agreements Fig 10 Box plot of the major actinide isotopes Results and discussion 4.1 Isotopic bias and uncertainty The calculated concentrations of all nuclides considered in the burnup credit analysis methodology (Table 1) were compared to measured concentrations obtained by destructive radiochemical analysis of the fuel samples The calculated concentrations correspond to the time of measurement of each isotope, with the exception of samples from Fukushima Daini-2 assembly 2F2DN23, which were back calculated by the laboratory to the time of discharge from the reactor One sample from the Fukushima Daini-2 assembly 2F2DN23, sample SF99-10, was not included in the analysis due to its very close proximity to the end of the active fuel column The results for this sample exhibited very large biases that are attributed to the spectral change near the ends of the fuel rods which are not accounted for in 2D models (DeHart et al., 2008) The deviations between the Polaris calculations (C) of nuclide content and measurements (M) are expressed as the relative percent Fig 11 Box plot of the minor actinides and fission products (Mo, Tc, Ru, Ag, and Rh) Table 10 Summary of Limerick GE11 × assembly measurements Assembly ID Rod ID Sample ID Fuel type Axial height (mm) Avg Void (%) Enrichment (wt % YJ1433 D8 D8-3D2 D8-4G3 D9-1D2 D9-2D2 D9-4D4 D9-4G1E1 H5-3A1C H5-3A1G UO2-Gd2O3 UO2-Gd2O3 UO2 UO2 UO2 UO2 UO2 UO2 823 1301 308 623 823 1305 308 623 54.8 68.8 12.1 44.1 65.4 69.1 54.8 57.7 3.60 3.60 3.95 3.95 3.95 3.95 3.95 3.95 D9 H5 118 235 U) Gd content (wt % Gd2O3) Burnup (GWd/MTU) 5.0 5.0 0 0 0 54.4 37.0 62.1 65.5 64.9 56.5 57.9 57.8 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek The statistical summary of the results for each nuclide are listed in Table 11, which includes the total number of measured samples available for each nuclide, the mean deviation, the standard deviation, the median value, minimum and maximum deviations, the 1st and 3rd quartiles (range contains 50% of the data points), and the P10 and P90 percentiles (range contains 80% of the data points) A similar analysis of PWR samples using the 2D TRITON sequence SCALE was performed by Ilas et al (2012) The present results for the BWR samples show similar trends with PWR analysis results However, for most nuclides, the standard deviation is larger for the BWR samples Applications to burnup credit The most widely used approach for burnup credit validation involves validating the separate components of the criticality safety analysis (Burnup Credit for LWR Fuel, 2008): components related to the prediction of spent fuel nuclide compositions and components associated with the criticality calculation Validation of the code prediction of nuclide compositions is routinely performed using experimental data from destructive radiochemical analysis of spent fuel samples Validation of the criticality calculation is frequently performed using applicable critical experiments Several different approaches have been developed and used to assess the effects of bias and uncertainty in predicted nuclide compositions on the keff of a criticality application model (Gauld, 2003) In the present study, the direct application of measured nuclide compositions and calculation compositions are used to assess uncertainties in criticality due to the nuclide composition (Wimmer, 2004) Fig 12 Box plot of the fission products (Nd, Cs, Sm, Eu, and Gd) difference (C/M – 1)% The distributions for these deviations are presented as box plots in Figs 10–12, showing the mean, median, quartiles, and box whiskers that represent the 10th (P10) and 90th (P90) percentiles of the data (this range contains 80% of the data points) and the min/max values (marked with asterisks) of the distributions The individual values for each sample are also shown Maximum values in 234 U, 238Pu, 242Pu, 241Am, 243Am and 109Ag percent differences are above 60% and are not shown in the plots in order to display distribution details These nonparametric plots are based on the actual deviations and make no assumptions about the statistical isotopic distributions (e.g., normality) An outlier analysis of these distributions could be performed; however, in this study, no data were rejected based on outlier analysis 5.1 Nuclide concentration model Criticality calculations were performed using the measured nuclide concentrations for each fuel sample using the application model Separately, criticality calculations were also performed using the same model, with nuclide concentrations calculated by Polaris for the same samples The nuclide concentrations were calculated using Polaris with best-estimate values of the irradiation parameters that were not Table 11 Statistical analysis of predicted isotopic concentrations (C/M-1) (%) Data No of Samples Mean Standard Deviation Median Minimum Maximum 1st Quartile (Q1) 3rd Quartile (Q3) 10th Percentile (P10) 90th Percentile (P90) 234 76 76 76 76 76 76 76 76 76 62 62 29 50 50 23 16 14 15 16 35 32 34 35 35 15 25 25 15 6.8% 4.3% 1.6% −0.1% 9.5% −0.9% −3.1% −3.3% 1.2% 2.8% 1.3% −2.4% 4.5% 2.5% 2.0% 25.5% 5.5% 31.0% −3.2% 0.2% −6.6% 2.6% −0.5% 4.7% −9.2% 6.3% 13.9% 5.2% 13.4% 11.2% 4.8% 0.3% 21.1% 8.7% 8.4% 11.6% 17.2% 17.4% 33.5% 11.9% 4.0% 3.2% 7.7% 15.5% 13.4% 38.1% 7.2% 8.2% 12.2% 6.6% 11.9% 6.5% 21.8% 3.7% 12.8% 9.0% 5.5% 2.8% 1.2% −0.1% 6.7% −1.0% −2.4% −2.4% 1.2% 3.6% −7.5% −5.7% 3.9% 1.4% −0.4% 23.3% 4.2% 20.2% −2.9% 1.6% −6.7% 3.3% −0.2% 6.0% 3.2% 6.0% 10.0% 2.5% −37.0% −15.1% −6.0% −0.8% −38.8% −22.8% −28.3% −34.5% −42.6% −50.3% −44.5% −19.8% −4.1% −2.5% −11.5% −4.3% −4.7% −17.8% −24.0% −17.0% −34.0% −10.4% −18.2% −8.5% −48.4% −3.2% −8.5% −6.2% 66.6% 36.5% 15.7% 0.5% 93.6% 22.7% 31.4% 40.1% 87.9% 69.1% 122.8% 46.4% 13.1% 11.8% 17.6% 49.5% 48.8% 147.2% 7.7% 17.0% 20.2% 15.8% 37.9% 13.6% 11.7% 14.0% 6.0% 31.1% 1.4% −2.8% −1.5% −0.2% −1.9% −6.6% −6.9% −8.8% −4.5% −5.0% −16.6% −7.7% 2.1% 0.7% −3.1% 14.6% −2.2% 12.7% −5.0% −4.8% −16.6% −4.2% −10.0% 0.7% −32.7% 4.7% 10.0% 1.1% 9.9% 9.1% 3.2% 0.1% 20.1% 4.4% −0.5% 2.9% 9.6% 10.5% 4.9% −1.1% 7.0% 3.6% 5.0% 38.7% 7.4% 46.4% 1.7% 6.0% 1.6% 7.5% 4.9% 10.2% 7.7% 9.2% 19.9% 5.0% −5.4% −8.1% −3.4% −0.6% −18.1% −11.6% −12.6% −17.6% −19.8% −15.2% −26.7% −11.3% 0.0% −0.8% −4.8% 6.0% −3.3% −4.5% −11.9% −10.8% −20.2% −8.1% −12.7% −7.1% −39.3% 0.6% 50.4% −0.3% 20.6% 22.0% 7.7% 0.2% 33.2% 10.2% 6.5% 9.2% 15.1% 15.6% 49.9% 6.1% 10.8% 8.0% 14.5% 45.3% 9.5% 54.5% 3.6% 7.7% 5.6% 9.6% 14.4% 12.2% 9.3% 10.3% 4.0% 20.2% U U U 238 U 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 241 Am 243 Am 237 Np 143 Nd 145 Nd 95 Mo 99 Tc 101 Ru 109 Ag 133 Cs 147 Sm 149 Sm 150 Sm 151 Sm 152 Sm 151 Eu 153 Eu 155 Gd 103 Rh 235 236 119 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Detailed Irradiation History Information for Radiochemical Assay Sample Measured Isotopic Concentrations for Radiochemical Assay Sample Stainless steel Water Calculate Isotopic Concentrations with Polaris Calculate for KENO Criticality Model Fig 14 Radial view of the KENO V.a GBC-68 cask model (elevation of vanished lattice) Calculate for KENO Criticality Model bias value for each sample, this procedure generated minimum and maximum bounding keff values (since the missing fission products are all neutron absorbers) that reflect the potential uncertainty due to the use of surrogate concentrations in the keff calculations Measurements of all major actinides were available for most samples considered in this report, with the exception of 14 samples that did not measure 241Am Measurements for minor actinides and fission products were available for a reduced number of samples The number of sample measurements available for each nuclide is given in Table 11 Calculate Difference Values Between - If If 5.2 Cask application model > 0.0 calculation overpredicts < 0.0 calculation underpredicts The GE14 fuel assembly is used as the reference design for these studies It is a common assembly design used in US BWRs, and it includes advanced geometry features seen in modern BWR fuel assemblies (e.g., large water rods, partial length rods, relatively high enrichment, and use of gadolinium-bearing fuel rods) The computational benchmark model developed by Mueller et al (2013) as a generic burnup credit (GBC) cask containing 68 BWR assemblies (GBC-68 cask) was used to quantify the impact of isotopic bias and uncertainty in the criticality analysis The cask was modeled using the KENO V.a Monte Carlo criticality code (Fig 14) The GBC-68 cask model assumes that all fuel rods contain the same nuclide compositions both axially and radially Axial variations (i.e., the natural uranium blanket regions) or enrichment zoning of the fuel rods in the assembly were not modeled These modeling assumptions that were used in the present study have been used previously in BWR criticality studies (Marshall et al., 2016) Fig 13 Uncertainty analysis methodology for nuclide compositions (adapted from (Wells, 2004)) adjusted for conservatism in the calculations The difference between the keff obtained using measurements (k m eff ) and the keff from calculations (k ceff ) provides a direct measure of the net impact (Δkeff bias) associated with the spent fuel nuclide calculations The calculational procedure is illustrated in Fig 13 Statistical analysis of a sufficient set of representative fuel samples can then be used to develop appropriate estimates of uncertainty and margins for criticality safety By applying nuclide measurements in the application model, the validation method relies directly on experimental measurements This method also inherently addresses potential correlations in the measured nuclide concentrations However, the results will also include a component of uncertainty that is associated with the measurements and is not easily separated from other components of uncertainty The impact of measurement uncertainties is estimated in Section 5.3 of this paper A common set of major actinides and actinides plus fission products (Table 1) were used in all criticality calculations Fuel compositions also included oxygen in the UO2 fuel matrix For the application of measurement data to the criticality model, measured nuclide concentrations in units of mg/gUi were converted to atom number densities using a fuel density of 10.42 g/cm3 To account for nuclides that were not measured in some samples, calculated concentrations were used as surrogate data for missing measurements The calculated nuclide concentrations used for surrogate data were adjusted to account for bias using the median bias derived from other samples with measured data (Table 11) The median provides a better statistical measure of population centrality for nonnormal distributions and in the presence of outliers To account for uncertainty in these estimated concentrations, additional keff calculations were performed using surrogate nuclide concentrations that were adjusted for uncertainty using the P10 and the P90 percentiles of the deviations obtained between calculated and measured nuclide concentrations listed in Table 11 Therefore, in addition to obtaining a keff 5.3 Criticality calculations Criticality calculations were performed using the KENO V.a Monte Carlo neutron transport code with 252-group MG cross sections The KENO V.a calculations are accessed through the criticality safety analysis sequence (CSAS) in SCALE This sequence performs automated, problem-dependent cross section processing, followed by the KENO V.a calculation to solve the keff eigenvalue problem The measured nuclide concentrations were applied in the GBC-68 application model, and the keff values were calculated with KENO V.a using data from each of the 76 spent fuel sample measurements As discussed previously, three separate criticality calculations were performed using the measured data for each sample: Measured isotopic data plus calculated surrogate data for isotopes not measured in the sample, with surrogate data calculated based on the median isotopic bias Measured isotopic data with surrogate data calculated based on the P10 percentile values Measured isotopic data with surrogate data calculated based on the 120 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek Fig 15 keff bias for actinide-only and actinide-plus-fission products results fuel (NEA/NSC/WPNCS/DOC, 2011) Reported uncertainties can vary significantly between different laboratories depending on the uncertainty assessment methods and rigor, the degree of reliance on past experience, and the components of the measurement uncertainty that are included in the assessment For example, uncertainties can vary based on whether they include all steps of the analysis, starting with cutting and dissolution of fuel samples Due to the inconsistency of uncertainty estimates, measurement uncertainties were not used to weight the individual sample results in this study One sample from the Dodewaard reactor, DU1, was measured at independent laboratories at SCK·CEN and PSI A comparison of the keff results using these two measurement sets shows a difference of about 550 pcm that is attributed to the measurements alone P90 percentile values The calculated surrogate data were adjusted by simultaneously increasing (when the P90 values are applied) or simultaneously decreasing (when the P10 values are applied) all surrogate nuclide concentrations to provide a conservative estimate of this uncertainty component Fig 15 plots the Δkeff (bias) results for each sample as pcm (1 pcm = 10−5) Uncertainties associated with the use of surrogate data are shown as error bars Each sample data point is color coded to identify the associated reactor and assembly design In general, the actinide-only results are similar to the actinide-plus-fission product results These results can be statically analyzed to quantify the uncertainty associated with the isotopic calculations used in the spent fuel criticality model Trending on major fuel parameters—including fuel burnup, void fraction, or other parameters—can be performed, but this is not shown here No statistically significant trends were observed in the results shown in this paper Using a simplified statistical analysis of the data that pools the results without trending, the mean keff bias was determined to be 262 pcm for the actinide-only products and 120 pcm for the actinide plus-fission products The standard deviations were determined to be 1380 pcm for the actinide-only products and 1431 pcm for the actinideplus-fission products The corresponding 95/95 lower one-sided tolerance limit above which 95% of the population lies is −2453 pcm for actinides only and −2695 pcm for actinides plus fission products These values may be applied in developing margins for BWR isotopic uncertainty in burnup credit criticality calculations 5.4.2 Void fraction Void fraction information is calculated by the operator with time steps shorter than the cycle length The uncertainty in the void fraction has been estimated by comparing calculated to measured average void fractions Measurements analyzed by Morooka et al (1989) suggest a relative standard deviation of 5.3% and 6.3% for the predictive codes COBRA/BWR and THERMIT These values apply to the average void fraction within an axial segment of an assembly (node) The void distribution within the assembly flow channel is not uniform, and the uncertainty in local void in the vicinity of any single fuel rod can be larger than the uncertainty in the average node void level Studies suggest that the void fraction distribution in regions near the channel wall or corner and water rods can be 25% less than the average void fraction under some conditions (Inoue et al., 1995) However, the radial variability can depend significantly on the axial location within the assembly The impact of void fraction uncertainty during depletion on the kinf of the fuel in out-of-reactor conditions was previously estimated by Wagner et al (1999) For core average void fractions of typically 40%, a 10% uncertainty in the void fraction was shown to have a corresponding uncertainty in kinf of ∼ ± 300 pcm Studies performed in the present work investigated void uncertainties for fuel rod C3 of Fukushima Daini 1, assembly 2F1ZN3 Three samples, UB (bottom), UM (middle), and UT (top) were irradiated with void fractions of nominally 10%, 40%, and 70% Reanalysis of these samples using a ± 10% change on void fraction uncertainty resulted in a keff uncertainty up to ± 30, ± 600, and ± 300 pcm for these samples, with the largest sensitivity observed for the middle sample (40% void) Larger uncertainties may be present in the local void fraction for 5.4 Isotopic model uncertainties The deviations seen in Fig 15 include bias from the model and nuclear data library used in the depletion and criticality calculations, as well as uncertainties associated with the measurements and input data used in the depletion calculations These uncertainties are assessed in more detail in the following sections 5.4.1 Measurements Uncertainties in the measured nuclide concentrations are reported by the laboratories for all samples used in this study The uncertainty depends to a large extent on the measurement method, the type of instrument used for mass spectrometry, the type and accuracy of reference standards, and the isotopic concentration of the isotope in the 121 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek (Devida et al., 2004), and also from using uranium and plutonium in limited cases (Reager, 2003) Consequently, the sample burnup is not known precisely due to uncertainties in the nuclide measurements, the methods, and nuclear data used in the burnup derivation Uncertainty in the burnup, which is an input parameter in the depletion calculations, will affect the nuclide concentrations and the keff of the application model The impact of burnup uncertainty on keff was estimated using a sample UM (mid-axial height) from rod C3 of Fukushima Daini assembly 2F1ZN3 with an average void of 38% The uncertainty was evaluated at the end of each cycle of irradiation for five cycles to cover a range of sample burnups An uncertainty in burnup of nominally 2% was found to have a 200 pcm effect at low burnup and up to 600 pcm at high burnup for the GBC-68 criticality application model In the case of the Fukushima Daini data, for cases in which uncertainties in the sample burnup values of up to 6.5% were reported, the potential impact of keff can be as large as 2000 pcm The Fukushima Daini samples exhibit some of the larger variations in the analyzed data (Fig 15) Table 12 Summary of uncertainties Parameter Parameter uncertainty keff uncertainty (pcm) RCA measurements Fuel temperature 1%–5% 50 K 100 K 10% 25% 2% 6% — 550 100 200 300–600 1500 200–600 600–1800 ∼450–590 < 2100 Void fraction Sample burnup Nuclear data Total some fuel rods in an assembly In the case of 25% uncertainty, the impact on the calculated keff of up to 1500 pcm would be expected Two of the larger sample deviations are observed for Limerick samples from rod D8 This rod contained Gd2O3 and had a lower average power, so it may have experienced a lower local void fraction compared to other rods in the assembly While these deviations cannot be definitely associated with void uncertainty, the calculations significantly overestimate the keff for these samples This is consistent with an overestimate of the local void conditions for this rod 5.4.6 Nuclear data uncertainty A common source of uncertainty in all depletion calculations is the evaluated nuclear data Uncertainties for cross sections, fission yields and decay ratios are captured in covariance libraries These uncertainties can be propagated to depletion calculations using stochastic sampling Recent work by Williams et al (2013) shows that due to nuclear data uncertainties, 2–4% uncertainty can be observed in the predicted major actinide concentrations, and Wieselquist et al (2013) have shown that the uncertainty in keff from nuclear data alone can exceed 500 pcm 5.4.3 Void history Time-dependent nodal averaged void fraction information is generally provided with power and fuel temperature history However, as in the case of the Fukushima Daini-1 × – samples, some experiments only include void fraction distributions that are averaged over the lifetime of the fuel assembly Also, even when time-dependent data are available, some depletion codes may require cycle-averaged void fractions due to modeling limitations The impact of the effect of void fraction history on keff was analyzed using samples at the bottom (UB), middle (UM), and top (UT) elevations from Fukushima Daini-1 × – assembly 2F1ZN3 The samples were modeled with void fractions averaged over five cycles, and the calculated keff values were compared to those from the detailed timedependent void models While the changes in keff values were as large as 1500 pcm for the bottom (at 11% void fraction) and the top (at 60% void fraction) samples, keff only changed 150 pcm for the middle sample (at 40% void fraction) The small change in keff for the middle sample is expected, since the middle nodes exhibit the smallest variation in void fraction with respect to burnup averaged void fractions The uncertainty in keff due to lack of detailed void fraction history can be significant, but this is dependent on the sample’s location and the void fraction variations experienced during depletion 5.4.7 Summary of model uncertainties Uncertainties in both the measurements and the calculations contribute to the total uncertainty in the criticality model and the variations seen in Fig 15 The impact of the uncertainty for several main parameters on the calculated keff of the cask model are summarized in Table 12 The different parameter values reflect typical uncertainty and maximum uncertainty values The range of keff uncertainty values shown for some parameters reflects different sample burnup and void values When these uncertainties are combined, assuming they are independent and combined quadratically, the result is total uncertainty in the application model up to about 2100 The measurements represent a large source of the overall uncertainty in terms of the nuclide concentration values and the estimation of the sample burnup that is also derived from the measurements Summary and conclusions 5.4.4 Fuel temperature The fuel temperature is generally reported with the operating history data as obtained by core code calculations The uncertainty in these values has been estimated to be ± 50 °C when data are provided by the operator and ± 100 °C when values are estimated from other sources of information (OECD Nuclear Energy Agency, 2016) An analysis of Forsmark GE14 assembly GN592 samples was performed by increasing the average fuel temperature from 792 K to 950 K during the depletion analysis The impact on all axial sample positions was nominally pcm/°C in the criticality application model Therefore, even when assuming large uncertainties of 100 °C in the fuel temperature, the uncertainty in keff is no greater than 200 pcm This indicates that while fuel temperature is important, the impact is likely to be less than that from many other sources of uncertainty present in BWR depletion models Experimental RCA data from 76 BWR spent fuel samples were evaluated to estimate uncertainties in the predicted nuclide concentrations using the Polaris lattice physics code in SCALE In addition, these isotopic uncertainties were applied to calculate margins for uncertainty in burnup credit criticality calculations for a dry cask application model Isotopic measurements cover a wide range of modern assemblies, including × – 2, × – 4, × – 7, ATRIUM-9, GE11, and 10 × 10 designs, including GE14 SVEA-96, and SVEA-100 The measured data cover void conditions ranging up to 74% void and a burnup range from to 68 GWd/MTU Most of the measurement data used in this report were obtained from public references and information compiled and documented as part of the OECD/NEA SFCOMPO spent nuclear fuel measurement database Several datasets used in this study were obtained from proprietary programs These data may be made available in the future to support licensing applications through nondisclosure agreements The uncertainty analysis methodology used in this study can be 5.4.5 Sample burnup The reported burnup of each sample is usually derived from measurements of 148Nd (ASTM, 2012); 148Nd plus other fission products 122 Nuclear Engineering and Design 345 (2019) 110–124 I.C Gauld and U Mertyurek readily applied to other computational methods and data and to other criticality application models The methodology directly applies measurement and calculated nuclide concentrations to the application model to calculate the system keff Margins for isotopic uncertainty can be derived from a statistical analysis of the results This procedure, as applied to the major actinide-only calculations, requires only minimal analysis of the isotopic distributions of individual nuclides since most samples include measurements for all major actinide isotopes For minor actinide and fission product burnup credit, analysis of individual isotopic bias and uncertainty was used to develop surrogate isotope concentration data with uncertainties for isotopes not measured in a fuel sample By directly applying measurement data in the application model, the method inherently considers potential covariances in the measured nuclide concentrations The uncertainty analysis approach has been demonstrated in this report using SCALE 6.2.2 calculations with ENDF/B-VII.1 cross section data Specifically, depletion calculations were performed using the Polaris code, and criticality calculations were performed using the KENO V.a code for the GBC-68 dry storage cask model Therefore, while the results presented in this paper are specific to this code system and application model, the results are expected to be similar for other dry storage and transportation cask designs when using the same computer codes and cross section data The results obtained show a small mean bias of less than 300 pcm and a standard deviation of about 1400 pcm The lower one-sided 95/ 95 tolerance limits for the population of data are −2453 pcm for actinides only and −2695 pcm for actinides plus fission products The analysis presented in this paper suggests that a large component of the keff uncertainty is likely attributable to measurement and modeling uncertainties Further reduction of the keff uncertainties would likely require access to higher quality measurements with lower uncertainty and better operating history information for the measured samples determination: a comparison of different experimental methods, pp 106–113 Norway HOTLAB: European Hot Laboratories Research Capacities and Needs, HOTLAB Plenary Meeting, England, T.R., Rider, B.F., 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LWR Fuels, JAERI-Tech 2000-071 Japan Atomic Energy Research Institute (in Japanese) English translation published as report ORNL/TR-2001/01 Nakahara, Y., Suyama, K., Inagawa, J., Nagaishi, R., Kurosawa, S., Kohno, N., Onuki, M., Mochizuki, H., 2002 Nuclide composition benchmark data set for verifying burnup codes on spent light water reactor fuels Nucl Technol 137, 111–126 https://doi org/10.13182/NT02-2 Spent Fuel Assay Data for Isotopic Validation: State of the Art Report, NEA/NSC/WPNCS/ DOC (2011) 5, OECD Nuclear Energy Agency, 2011 OECD Nuclear Energy Agency, 2016 Evaluation Guide for the Evaluated Spent Nuclear Fuel Assay Database (SFCOMPO), NEA/NSC/R 2015, OECD/NEA Working Party on Nuclear Criticality Safety, Expert Group on Assay Data for Spent Nuclear Fuel < https://www.oecd-nea.org/science/wpncs/ADSNF/index html > Ortego, P., Rodríguez, A., 2013 Evaluation of Dodewaard DU1 Sample, report prepared for the OECD/NEA Expert Group on Assay Data for Spent Nuclear Fuel SEA Ingeniería 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Yamamoto, T., 2012 Compilation of Measurement and Analysis Results of Isotopic Inventories of Spent BWR Fuels, report contributed to the OECD/NEA and included as part of the SFCOMPO spent fuel. .. spent fuel criticality safety analyses using burnup credit The range of application applies to BWR fuel burnup beyond the region of peak reactivity that is associated with the use (depletion) of fuel. .. Investigation of Burnup Credit Modeling Issues Associated with BWR Fuel ORNL/TM-1999/193 Oak Ridge National Laboratory Wells, A.H., 2004 Isotopic Model for Commercial SNF Burnup Credit, US Department of