Search

In this work, we explore the use of an iterative Bayesian Monte Carlo (iBMC) method for nuclear data evaluation within a TALYS Evaluated Nuclear Data Library (TENDL) framework. The goal is to probe the model and parameter space of the TALYS code system to find the optimal model and parameter sets that reproduces selected experimental data. The method involves the simultaneous variation of many nuclear reaction models as well as their parameters included in the TALYS code. The ‘best’ model set with its parameter set was obtained by comparing model calculations with selected experimental data. Three experimental data types were used: (1) reaction cross sections, (2) residual production cross sections, and (3) the elastic angular distributions. To improve our fit to experimental data, we update our ‘best’ parameter set—the file that maximizes the likelihood function—in an iterative fashion. Convergence was determined by monitoring the evolution of the maximum likelihood estimate (MLE) values and was considered reached when the relative change in the MLE for the last two iterations was within 5%. Once the final ‘best’ file is identified, we infer parameter uncertainties and covariance information to this file by varying model parameters around this file. In this way, we ensured that the parameter distributions are centered on our evaluation. The proposed method was applied to the evaluation of p+$$^{59}$$ 59 Co between 1 and 100 MeV. Finally, the adjusted files were compared with experimental data from the EXFOR database as well as with evaluations from the TENDL-2019, JENDL/He-2007 and JENDL-4.0/HE nuclear data libraries.

This paper presents an improved uncertainty quantification technique for the validation of CASMO-5 on the spent fuel reactivity worth experiments of the LWR-PROTEUS Phase II program. In the program, eleven spent fuel samples manufactured from rods irradiated in a Swiss PWR (discharge burnups of 20–120 MWd/kg) were measured in the PROTEUS research reactor. In this work, both irradiation and reactivity worth measurement steps were modeled with CASMO-5 and the uncertainty on the code prediction were calculated using SHARK-X. For the first time in this work, we propagated the nuclear data uncertainties coming from cross-sections and fission yields for all samples in both fuel irradiations and the reactivity worth experiment models. We found that the fission yield and cross section uncertainties have similar contributions to the uncertainty of the reactivity worth prediction and that the reactivity worth probability distribution is non-normal because of the non-normal distribution of the perturbed fission yield data produced by the GEF code. Propagating input uncertainties through fuel irradiation as well as considering fission yield uncertainty led to larger computational uncertainty than previously reported. However, the observed trends with respect to exposure, fuel type, and moderating conditions are similar. In particular, a linear regression analysis showed that the predictions of reactivity with exposure by CASMO-5 are very accurate for various moderating conditions and for very high burnup. Finally, we estimated the effects of the irradiation history specifications on the relative reactivity worth bias and its uncertainty using two independent irradiation histories. While the bias uncertainty coming from uncertain cross sections was similar when considering either irradiation histories, we observed differences in the bias value. The irradiation history specification is a significant source of modeling bias and should be further investigated.

This study presents an analysis of the ARIANE GU3 sample, in terms of nuclide inventory, as well as sample rod and assembly decay heat. The validation of a number of CASMO5 and library versions are performed with regards to the measured nuclide inventory, taking into account two dimensional lattice simulations. Uncertainties due to various sources (nuclear data, operating conditions and manufacturing tolerances) are also provided, and are combined with biases into expanded uncertainties. This study is similar to a previous one on the GU1 sample and fit in the framework of code validation, as well as in the estimation of code predictive power for spent fuel characterization.

The present study provides a detailed analysis of the calculations of 50 isotopic compositions for the Post Irradiation Examination sample GU1 from the ARIANE program. Two types of approach are performed: a lattice (2 dimensional) and a full core (3 dimensional) calculations. In the case of lattice calculations, the effect oflocation is also studied. Different code versions (for CASMO5 and SNF) are used in order to contribute to the validation work for specific calculation schemes and to assess the impact of nuclear data libraries as well. The effects of nuclear data are also quantified for cross sections, spectra and fission yields, together with their partial contributions. It is concluded that the consideration of the effect of the mass balance, nuclear data uncertainties, as well as uncertainties from operational conditions and manufacturing tolerances help in obtaining consistency between calculated and measured isotopic concentrations. This study is then complemented with decay heat calculations for the assembly of interest, consistent with the PIE study. It indicates that, without considering geometrical deformation due to the long storage time, nuclear data are still the main source of uncertainties. Expanded uncertainties (including biases, experimental and calculation uncertainties) are finally proposed for both isotopic compositions and decay heat.

The effect of nuclear data (fission yields, cross sections and emitted spectra) is quantified for spent nuclear fuel assemblies from a realistic boiling water reactor operated over 25 cycles. Nominal calculations are performed with the CASMO5, SIMULATE-3 and SNF codes and the ENDF/B-VII.0 nuclear data library. The uncertainties are calculated with the same codes, using a Monte Carlo propagation method, and the ENDF/B-VII.1 covariance matrices. The conclusions are that (1) the nuclear data have a non-negligible impact for spent fuel quantities (e.g., decay heat, neutron emission or isotopic contents); (2) the importance of varying all data together is demonstrated, showing an under- or overestimation of uncertainties if fission yields are sampled separately from the other nuclear data; and finally (3) the importance of considering the full irradiation history (multi-cycle assembly life) is also demonstrated, showing also an under- or overestimation of uncertainties when performing the nuclear data sampling for a single reactor cycle.

This research aims at validating the SIMULATE-3K code and complementing the results with the quantification of nuclear data uncertainties against the Special Power Excursion Reactor Test III (SPERT-III) experiments. To that aim, the SHARK-X methodology, under development at PSI, for the propagation of nuclear data uncertainties in CASMO5 2-D lattice calculations to 3-D core transient simulations is applied for the analysis of a SPERT-III super-prompt critical test conducted at cold startup conditions. Concerning transient results, both total power and reactivity show a good agreement with the measurements at the initial phase of power excursion, while a slight discrepancy is obtained at the final phase of the transient. The estimated uncertainties regarding both steady-state parameters such as k-eff and static reactivity worth, as well as dynamical quantities such as power pulse width and enthalpies are presented. Results show non-negligible sensitivity upon the employed nuclear data library. The uncertainty quantification results show relatively small biases for k-eff and reactivity. The uncertainty in peak power is around 3%, while it is negligible for the time to peak power and the pulse width. The time evolution of the standard deviation and skewness of the total power showed special shapes with relatively high maximum values. In addition, the uncertainty due to nuclear data in the two important safety parameters, i.e. maximum nodal fuel temperature and enthalpy reaches maximum value around 2% and 10%, respectively.

In view of massive operations with LWR spent nuclear fuel for the forthcoming final geological disposal, as expected, e.g., in Switzerland, needs are growing for exhaustive and enhanced criticality safety assessments to allow optimization of the spent nuclear fuel transportation, storage and disposal strategies. At the Paul Scherrer Institute (PSI) the current base methodology for criticality safety evaluations (CSE) used for Swiss applications is focused, following common practices, on establishing an upper subcritical limit (USL) for the effective neutron multiplication factor ( k eff ) , based on a statistical evaluation of the obtained validation results in terms of the calculated-to-benchmark k eff values. Recently, new calculation capabilities have been developed at PSI in particular to propagate neutron-nuclear data (ND) uncertainties in calculations with Monte Carlo transport codes in combination with general-purpose ND libraries. The computation tool NUSS for random sampling the ACE formatted ND libraries was developed for that purpose. Thereby, this paper concerns how these new calculation capacities could improve the present PSI CSE methodology and the prospects for its upgrading towards burnup credit applications are consequently discussed.

At the Paul Scherrer Institut, the development of the SHARK-X methodology to propagate nuclear data uncertainties in CASMO-5 2-D assembly depletion calculations started few years ago. Before that, the CMSYS platform had been established to serve as framework for the continuous development and validation of core models based on CASMO/SIMULATE for all the Swiss operating reactors and cycles. Recently, a first attempt to integrate SHARK-X within CMSYS was initiated in order to complement the core analyses with nuclear data uncertainty quantifications. A proof-of-principle is presented in this paper on the basis of real operated UO2 and MOX cycles of a Swiss PWR plant. In this framework, the nuclear data uncertainties related to cross-sections, neutron multiplicity and fission spectrum, provided via SCALE-6.2b4 based variance-covariance matrices, are propagated using the stochastic sampling method in all types of core calculations, including cycle depletion, validation against flux measurements and safety calculations typically required for reload licensing. For each calculation type and core design, the statistical convergence of relevant quantities of interest is studied in order to determine the required optimal number of samples. Thereafter, the uncertainties of selected quantities of interest are presented and compared between both core designs. For instance, the estimated uncertainties are shown for critical boron concentration as well as 3-D power/burnup distributions for cycle depletion analyses. Regarding the validation of the core models against in-core detector measurements, the uncertainties in biases between calculated and experimental 3-D reaction rates are also evaluated. Finally, for calculations of safety parameters related to core design and licensing, uncertainties in reactivity coefficients, control rod worths and kinetic parameters are presented.

The current research summarizes recent developments performed within the PSI BEPU methodology and the corresponding results on the SPERT-III RIA experiments. In this regard, three main studies have been carried out. First, an uncertainty breakdown study has been performed in order to identify the dominant nuclear data and to quantify their respective contributions to the overall uncertainties of the parameters of interest. On the other hand, the second study was devoted to assess the impact of considering the effect of cross section perturbation (limited for the time being to U-238 capture) in the resonance self-shielding calculation, known as the implicit effect, on different parameters’ uncertainties in SPERT-III RIA transient. Finally, the third study was conducted with the main goal to assess the impact of kinetic parameter uncertainties, such as delayed neutron yields and associated decay constants, on the overall uncertainties. The uncertainty quantification results of the first study, based on the ENDF/B-VII.1 library, showed that, for steady-state, the first dominant contributor to the overall uncertainties of the static reactivity worth and k-eff is U-235 nubar, followed by U-238 then U-235 capture cross sections. However, for the transient, the first dominant contributor to the overall uncertainties, in e.g. total power and reactivity, is the U-238 inelastic scattering. More interestingly, it was found that, the second dominant contribution to the overall power uncertainty, during the initial excursion phase, is due to the U-235 nubar, while during the power reversal phase, the U-238 capture becomes the second dominant contribution, and even the first one by the end of the transient. Moreover, results of the second study demonstrated a clear systematic decrease of the uncertainty of all parameters due to the inclusion of the implicit effect. In steady state, due to the impact of the implicit effect, the Doppler coefficient relative uncertainty could be reduced up to 30%, which is reflected in the transient, especially in the reversal phase of the power excursion where Doppler effect plays a key role, by a systematic decrease of the relative uncertainty of total power and other parameters. Finally, in the third study, the estimated uncertainties, regarding both steady-state and transient parameters, have shown systematic larger values due to kinetic parameter uncertainties compared to those due to the other nuclear data.

Presently, a criticality safety evaluation methodology for the final geological disposal of Swiss spent nuclear fuel is under development at the Paul Scherrer Institute in collaboration with the Swiss National Technical Competence Centre in the field of deep geological disposal of radioactive waste. This method in essence pursues a best estimate plus uncertainty approach and includes burnup credit. Burnup credit is applied by means of a computational scheme called BUCSS-R (Burnup Credit System for the Swiss Reactors–Repository case) which is complemented by the quantification of uncertainties from various sources. BUCSS-R consists in depletion, decay and criticality calculations with CASMO5, SERPENT2 and MCNP6, respectively, determining the keff eigenvalues of the disposal canister loaded with the Swiss spent nuclear fuel assemblies. However, the depletion calculation in the first and the criticality calculation in the third step, in particular, are subject to uncertainties in the nuclear data input. In previous studies, the effects of these nuclear data-related uncertainties on obtained keff values, stemming from each of the two steps, have been quantified independently. Both contributions to the overall uncertainty in the calculated keff values have, therefore, been considered as fully correlated leading to an overly conservative estimation of total uncertainties. This study presents a consistent approach eliminating the need to assume and take into account unrealistically strong correlations in the keff results. The nuclear data uncertainty quantification for both depletion and criticality calculation is now performed at once using one and the same set of perturbation factors for uncertainty propagation through the corresponding calculation steps of the evaluation method. The present results reveal the overestimation of nuclear data-related uncertainties by the previous approach, in particular for spent nuclear fuel with a high burn-up, and underline the importance of consistent nuclear data uncertainty quantification methods. However, only canister loadings with UO2 fuel assemblies are considered, not offering insights into potentially different trends in nuclear data-related uncertainties for mixed oxide fuel assemblies.

This paper presents preliminary criticality safety assessments performed by the Paul Scherrer Institute (PSI) in cooperation with the Swiss National Cooperative for the Disposal of Radioactive Waste (Nagra) for spent nuclear fuel disposal canisters loaded with Swiss Pressurized Water Reactor (PWR) UO2 spent fuel assemblies. The burnup credit application is examined with respect to both existing concepts: taking into account actinides only and taking into account actinides plus fission products. The criticality safety calculations are integrated with uncertainty quantifications that are as detailed as possible, accounting for the uncertainties in the nuclear data used, fuel assembly and disposal canister design parameters and operating conditions, as well as the radiation-induced changes in the fuel assembly geometry. Furthermore, the most penalising axial and radial burnup profiles and the most reactive fuel loading configuration for the canisters were taken into account accordingly. The results of the study are presented with the help of loading curves showing what minimum average fuel assembly burnup is required for the given initial fuel enrichment of fresh fuel assemblies to ensure that the effective neutron multiplication factor, k e f f , of the canister would comply with the imposed criticality safety criterion.

International audience; This paper presents an application of the Backward-Forward Monte Carlo (BFMC) method using measured critical boron concentrations for a specific PWR cycle. The considered prior nuclear data are the fission cross sections, $\overline{\nu}_{p}$ for$^{235}$U and$^{239}$Pu and the capture cross section of$^{238}$U. The posterior nuclear data exhibit cross-isotope correlations, moderate changes for the average quantities and reduced uncertainties. This work is the first one considering the BFMC method and an integral system mostly sensitive to thermal neutrons. It contributes to show the impact of integral experimental data for the evaluation of nuclear data and their covariance matrices, leading to cross-isotope correlations and a nuclear data uncertainty reduction.

International audience; In this paper, we present three Monte Carlo methods to include integral benchmark information into the nuclear data evaluation procedure: BMC, BFMC and Mocaba. They allow to provide posterior nuclear data and their covariance information in a Bayesian sense. Different examples will be presented, based on 14 integral quantities with fast neutron spectra (k$_{eff}$ and spectral indices). Updated nuclear data for$^{235}$U,$^{238}$U and$^{239}$Pu are considered and the posterior nuclear data are tested with MCNP simulations. One of the noticeable outcomes is the reduction of uncertainties for integral quantities, obtained from the reduction of the nuclear data uncertainties and from the rise of correlations between cross sections of different isotopes. Finally, the posterior nuclear data are tested on an independent set of benchmarks, showing the limit of the adjustment methods and the necessity for selecting well representative systems.

The CASMO/SIMULATE/MCNP/FISPACT-II calculation route has been established at the Paul Scherrer Institute (PSI) for reactor dosimetry and activation studies. Furthermore, the in-house tool NUSS is in use at PSI for nuclear data (ND) related uncertainties quantifications with Monte Carlo neutron transport calculations. The use of randomly sampled ACE-formatted ND files not only allows propagation of the ND uncertainties, but also can serve for assessing the applicability of different types of experimental data for validation of calculation predictions of parameters of interest. In the present work an application of the PSI calculation scheme for analysis of activation reaction rates and the fast neutron fluence (FNF), throughout the Swiss pressurised water reactor (PWR) and simplified containment building models, is demonstrated. As particular examples of potentially available experimental data, two kinds of the neutron flux monitors are considered: a) the reactor pressure vessel scraping samples and detectors placed in the dosimetry channels, mounted at the core barrel and designed for validation of FNF calculations, and b) the ex-vessel dosimeters, specifically used by the Swiss waste management organisation (NAGRA) for validation of bio-shield activation predictions. The calculations were done with the ENDF/B-VII.1 library. The obtained results demonstrate importance of the ND uncertainties for the dosimetry evaluations. The assessment of the applicability of the selected experimental information for validation of the bio-shield irradiation calculations was done based on evaluation of the ND-related Pearson correlation coefficients.

This paper describes the effect of input uncertainties on a set of integral parameters (kinf, nuclide compositions) associated with the validation of CASMO-5 against PIE data. The nuclear data under consideration are the cross-sections, fission spectrum and neutron multiplicities and fission yields. Various sources of covariance information are considered, novel ones (ENDFB-VIII.0, JEFF-3.3) as well as more widely distributed ones (JENDL-4.0, ENDF/B-VII.1, Scale 6.1 and Scale 6.2). All possible nuclide reaction pairs (cross sections, fission spectrum and averaged number of neutron per fission) have been perturbed, e.g. all isotopes available in both the respective covariance libraries and the CASMO-5 library. The evolution of the uncertainty estimates with exposure is complemented with sensitivity analysis to determine the main contributors to the uncertainty. The Pearson coefficient defined between the model output and a given input is used in this work to assess the part of the variance in the model output coming from the considered input uncertainty. It is a very promising measure of sensitivity as it is computationally cheap even though it assumes linearity of the output with respect to input perturbations. The evolution of the uncertainty with exposure, both in terms of trends and magnitude are however very different. Sensitivity analysis allows determining why the trends and magnitudes are different.

The Mixed Oxide samples (MOX) ARIANE Post Irradiation Examination samples BM1 and BM3 have been analyzed in this work, based on various two- and three-dimensional models. Calculated and measured nuclide inventories are compared based on CASMO5, SIMULATE and SNF simulations, and calculated values for the decay heat of the assembly containing the samples are also provided. For uncertainty propagation, the covariance information from three different nuclear data libraries are used. Uncertainties from manufacturing tolerances and operating conditions are also considered. The results from these two samples are compared with the ones from two UO2 samples, namely GU1 and GU3, also from the ARIANE program, applying the same calculation scheme and uncertainty assumptions. It is shown that a two-dimensional assembly model provides better agreement with the measurements than a two-dimensional single pin model, and that the full core three-dimensional model provides similar results compared to the assembly model, although no 148Nd normalization is applied for the full core model. For the MOX assembly decay heat, as expected, heavy actinides have a higher contribution compared to the cases with the UO2 samples; additionally, decay heat uncertainties are moderately smaller in the case of the MOX assembly.

The effects of the nuclear data uncertainties are quantified for specific core parameters from a real Boiling Water Reactor operated over 25 consecutive cycles. Nominal calculations are performed with the CASMO5 and SIMULATE-3 codes and the ENDF/B-VII.0 nuclear data libraries. The uncertainties are calculated using a Monte Carlo propagation method, and the ENDF/B-VII.1 covariance matrices. The conclusions are that the nuclear data uncertainties (1) have a limited impact on core parameters (axial power, linear heat generation rate, and comparison with in-core measurements), but (2) are larger for keff compared to the expectations from reactor experience. Additionally, the importance of simultaneously varying all input data in order to accurately calculate uncertainties is demonstrated.

In this paper the isotopic content of the U1 sample is re-analyzed taking into account the full irradiation environment with a 3-dimensional core simulator. It is found that by accounting for the neighboring assemblies as well as the various axial segments, the agreement between the measured and calculated isotopic concentrations is greatly improved. Additionally, the sample burnup is impacted (reduced) compared to the previous studies. Varying nuclear data and code versions, an estimation of uncertainties is proposed. Finally, remarks about the U1 relevance for the estimation of the biases for assembly averaged quantities are presented.

NUSS-RF is a tool for nuclear data uncertainty propagation through neutronics calculations with continuous-energy Monte Carlo codes and ACE-formatted nuclear data libraries. Many existing codes, in...

Nuclear data uncertainty propagation plays a growing role in neutronic simulation by giving confidence bounds to physical macroscopic parameters used for safety and design of nuclear systems. This study deals with nuclear data uncertainty propagation (cross-sections, fission spectrum, neutron multiplicities and fission yields) on the nuclide composition of two UO2 spent fuel samples of different burnup. In order to perturb the fission yields in a neutron lattice physics code, the perturbation methodology combines an external correlation matrix to the standard deviations available in the international evaluations. The resulting matrix is normalized to fit to physical constraints. Then the impacts of nuclear data uncertainties on the k-inf are assessed and the main contributors are highlighted. Two different sources of uncertainty for the cross-sections and the fission yields are compared showing the large effect of the input uncertainty. The actinides and fission products composition of the two samples after depletion are sorted according to the main uncertainty origin of their C/E (experimental, cross-sections, fission yields). Special attention is paid to the Nd-148 C/E comparisons as these results show the need for improvement of the Nd-147 capture uncertainties.

This work is presenting a comparison of results for different methods of uncertainty propagation due to nuclear data for 330 criticality-safety benchmarks. Covariance information is propagated to keff using either Monte Carlo methods (NUSS: based on existing nuclear data covariances, and TMC: based on reaction model parameters) or sensitivity calculations from MCNP6 coupled with nuclear data covariances. We are showing that all three methods are globally equivalent for criticality calculations considering the two first moments of a distribution (average and standard deviation), but the Monte Carlo methods lead to actual probability distributions, where the third moment (skewness) should not be ignored for safety assessments.

In this work, a method is proposed for combining differential and integral benchmark experimental data within a Bayesian framework for nuclear data adjustments and multi-level uncertainty propagation, using the Total Monte Carlo method. First, input parameters to basic nuclear physics models implemented within the TALYS code, were randomly varied to produce a large set of random nuclear data files. Next, a probabilistic data assimilation was carried out by computing the likelihood function for each random nuclear data file based first on only differential experimental data and then on integral benchmark data. The individual likelihood functions from the two updates were then combined into a global likelihood function. The proposed method was applied for the adjustment of n+208Pb in the fast energy region below 20 MeV. The adjusted file was compared with available experimental data as well as evaluations from the major nuclear data libraries and found to compare favourably.

A lot of research work has been carried out in fine tuning model parameters to reproduce experimental data for neutron induced reactions. This however is not the case for proton induced reactions where large deviations still exist between model calculations and experiments for some cross sections. In this work, we present a method for searching both the model and model parameter space in order to identify the 'best' nuclear reaction models with their parameter sets that reproduces carefully selected experimental data. Three sets of experimental data from EXFOR are used in this work: (1) cross sections of the target nucleus (2) cross sections of the residual nuclei and (3) angular distributions. Selected models and their parameters were varied simultaneously to produce a large set of random nuclear data files. The goodness of fit between our adjustments and experimental data was achieved by computing a global reduced chi square which took into consideration the above listed experimental data. The method has been applied for the adjustment of proton induced reactions on Co-59 between 1 to 100 MeV. The adjusted files obtained are compared with available experimental data and evaluations from other nuclear data libraries., Comment: 2019 International Conference On Nuclear Data for Science and Technology

In this work, an overview on the relevance of the nuclear data (ND) uncertainties with respect to the Light Water Reactors (LWR) neutron dosimetry is presented. The paper summarizes results of several studies realized at the LRT laboratory of the Paul Scherrer Institute over the past decade. The studies were done using the base LRT calculation methodology for dosimetry assessments, which involves the neutron source distribution representation, obtained based on validated CASMO/SIMULATE core follow calculation models, and the subsequent neutron transport simulations with the MCNP® software. The methodology was validated using as reference data results of numerous measurement programs fulfilled at Swiss NPPs. Namely, the following experimental programs are considered in the given overview: PWR “gradient probes” and BWR fast neutron fluence (FNF) monitors post irradiation examination (PIE). For the both cases, assessments of the nuclear data related uncertainties were performed. When appropriate, a cross-verification of the deterministic and stochastic based uncertainty propagation techniques is provided. Furthermore, the observations on which particular neutron induced reactions contribute dominantly to the overall ND-related uncertainties are demonstrated. The presented results should help with assessing the overall impact of the various nuclear data uncertainties with respect to dosimetry applications and provide relevant feedback to the nuclear data evaluators.

This paper presents a Bayesian approach based on integral experiments to create correlations between different isotopes which do not appear with differential data. A simple Bayesian set of equations is presented with random nuclear data, similarly to the usual methods applied with differential data. As a consequence, updated nuclear data (cross sections, [see formula in PDF], fission neutron spectra and covariance matrices) are obtained, leading to better integral results. An example for 235U and 238U is proposed taking into account the Bigten criticality benchmark.

At the Paul Scherrer Institute (PSI), a computational scheme aimed at high fidelity fast neutron fluence estimations for Light-Water-Reactors (LWRs) was in previous years developed. In this scheme, the neutron transport calculations are performed with the stochastic Monte Carlo N-Particle Transport Code MCNPX using as basis a three-dimensional pin-level volumetric source obtained from validated deterministic CASMO/SIMULATE models. While first validation studies confirmed a satisfactory performance, the strategy is to continually add new validation cases in order to achieve an enlarged and comprehensive qualification basis that also integrates latest advances in methods and/or nuclear data. Thereby, new sets of experimental data from a Swiss operating pressurized water reactor plant that became available recently were adopted for a further validation of the scheme. The first set consists of Mn-54 and Nb-93m activity measurements from so-called gradient probes located at an elevation corresponding to the top end of active fuel and increasing thereby the computational challenges because of very strong axial flux gradients. The second set consists of fluence estimates derived from Mn-54 and Nb-93m activity measurements of scraping samples extracted from the reactor pressure vessel. All dosimeters have been analyzed after the 27th cycle of operation of the reactor, providing thereby an opportunity to assess the computational methodology for modern fuel management schemes. This paper presents the validation study of the PSI fast neutron fluence scheme against these two new experimental sets including scheme adaptations and optimizations that were implemented to that aim. In particular, a new variance reduction approach, easily adaptable to any location but established here in order to tackle the challenging features of the gradient probe locations, is outlined. (C) 2015 Elsevier Ltd. All rights reserved.

The “blackbox” approach of stochastic sampling (SS) methods for simultaneous nuclear data uncertainty quantification is powerful except it reveals little of the individual uncertainty contributions...

Stochastic sampling (SS) method for quantifying nuclear data uncertainties is accomplished by using perturbed nuclear data in routine neutronics calculations and determining the variance of output parameters due to the input nuclear data uncertainties. Existing SS-based methods have demonstrated the feasibility and efficiency of propagating uncertainties in multigroup nuclear data. However, in fields such as criticality safety assessment, pointwise representation of nuclear data is more appropriate in order to corroborate the increasing safety demand and best-estimate modeling capabilities. In this work, an SS-based tool, called NUSS is implemented which perturbs pointwise ACE-formatted nuclear data using multigroup nuclear data covariance. The use of pointwise ACE-formatted nuclear data in NUSS can accommodate flexible multigroup covariance structures and allows for nuclear data uncertainty propagation through the continuous/pointwise-energy transport code MCNPX. As a first step of the NUSS development and verification, uncertainty contributions from 239 Pu and 235 U nuclear data were assessed for Jezebel (Pu-fueled) and Godiva (U-fueled) fast-spectrum criticality benchmarks. NUSS results are compared to those by other uncertainty quantification methods such as TSUNAMI and MCNPX PERT CARD. Next, Light Water Reactor (LWR) pin cell models from the OECD/NEA UAM Phase-1 benchmark were analyzed. Results of cross section and k inf uncertainties in consideration of different nuclear data covariance libraries are presented.

International audience; The impact of the current nuclear data library covariances such as in ENDF/B-VII.1, JEFF-3.2, JENDL-4.0, SCALE and TENDL, for relevant current reactors is presented in this work. The uncertainties due to nuclear data are calculated for existing PWR and BWR fuel assemblies (with burn-up up to 40 GWd/tHM, followed by 10 years of cooling time) and for a simplified PWR full core model (without burn-up) for quantities such as k∞ , macroscopic cross sections, pin power or isotope inventory. In this work, the method of propagation of uncertainties is based on random sampling of nuclear data, either from covariance files or directly from basic parameters. Additionally, possible biases on calculated quantities are investigated such as the self-shielding treatment. Different calculation schemes are used, based on CASMO, SCALE, DRAGON, MCNP or FISPACT-II, thus simulating real-life assignments for technical-support organizations. The outcome of such a study is a comparison of uncertainties with two consequences. One: although this study is not expected to lead to similar results between the involved calculation schemes, it provides an insight on what can happen when calculating uncertainties and allows to give some perspectives on the range of validity on these uncertainties. Two: it allows to dress a picture of the state of the knowledge as of today, using existing nuclear data library covariances and current methods.

This paper presents a Bayesian approach based on integral experiments to create correlations which do not appear with differential data. Some quantities such as the fission cross section (σ ), neutron multiplicity (ν p ), neutron spectra (χ ), etc. are usually neither modeled together nor measured in coincidence, thus there is no correlation matrices in evaluated nuclear data libraries. One can nevertheless use the information from integral experiments such as fast criticality-safety benchmarks to correlate such quantities for possible inclusion in nuclear data libraries. A simple Bayesian set of equations is presented with random nuclear data, similarly to the usual methods applied with differential data. An example for 239 Pu is proposed.

Nuclear data uncertainty propagation based on stochastic sampling ( SS) is becoming more attractive while leveraging modern computer power. Two variants of the SS approach are compared in this paper. The Total Monte Carlo (TMC) method by the Nuclear Research and Consultancy Group (NRG) generates perturbed ENDF-6-formatted nuclear data by varying nuclear reaction model parameters. At Paul Scherrer Institute (PSI) the Nuclear data Uncertainty Stochastic Sampling (NUSS) system generates perturbed ACE-formatted nuclear data files by applying multigroup nuclear data covariances onto pointwise ACE-formatted nuclear data. Uncertainties of Pu-239 and U-235 from ENDF/B-VII.1, ZZ-SCALE6/COVA-44G and TENDL covariance libraries are considered in NUSS and propagated in MCNPX calculations for well-studied Jezebel and Godiva fast spectrum critical benchmarks. The corresponding uncertainty results obtained by TMC are compared with NUSS results and the deterministic Sensitivity/Uncertainty method of TSUNAMI-3D from SCALE6 package is also applied to serve as a separate verification. The discrepancies in the propagated Pu-239 and U-235 uncertainties due to method and covariance differences are discussed.

At the Paul Scherrer Institut (PSI), a methodology for nuclear data uncertainty propagation in CASMO-5M (C5M) assembly calculations is under development. This paper presents a preliminary application of this methodology to C5M decay heat calculations. Applying a stochastic sampling method, nuclear decay data uncertainties are first propagated for the cooling phase only. Thereafter, the uncertainty propagation is enlarged to gradually account for cross-section as well as fission yield uncertainties during the depletion phase. On that basis, assembly heat load uncertainties as well as total uncertainty for the entire pool are quantified for cooling times up to one year. The relative contributions from the various types of nuclear data uncertainties are in this context also estimated.

The development of a high-fidelity computational scheme to estimate the accumulated fluence at the tips of PWR control rods (CR) has been initiated at the Paul Scherrer Institut (PSI). Both the fluence from high-energy ( E > 1 MeV ) neutrons as well as for the thermal range ( E 0.625 eV ) are required as these affect the CR integrity through stresses/strains induced by coupled clad embrittlement / absorber swelling phenomena. The concept of the PSI scheme under development is to provide from validated core analysis models, the volumetric neutron source to a full core MCNPX model that is then used to compute the neutron fluxes. A particular aspect that needs scrutiny is the ability of the MCNPX-based calculation methodology to accurately predict the flux shapes along the control rod surfaces, especially for fully withdrawn CRs. In that case, the tip is located a short distance above the core/reflector interface and since this situation corresponds to a large part of reactor operation, the accumulated fluence will highly depend on the achieved calculation accuracy and precision in this non-fueled zone. The objective of the work presented in this paper is to quantify the influence of nuclear data on the calculated fluxes at the CR tips by (1) conducting a systematic comparison of modern neutron cross-section libraries, including JENDL-4.0, JEFF-3.1.1 and ENDF/B-VII.0, and (2) by quantifying the uncertainties in the neutron flux calculations with the help of available neutron cross-section variances/covariances data. For completeness, the magnitude of these nuclear data-based uncertainties is also assessed in relation to the influence from other typical sources of modeling uncertainties/biases.

The paper presents recent activities conducted at the Paul Scherrer Institut (PSI) in relation to the development and validation of an integral calculation methodology based on CASMO-4/SIMULATE-3/MCNPX for accurate estimations of the fast neutron fluence (FNF) accumulated on reactor pressure vessels and internals of the operating Swiss BWRs. With this computational scheme, the default neutron source is set up at the pin-by-pin level with realistic spectrum specifications based on the actual reactor cycle-specific data from validated reference CASMO-4/SIMULATE-3 core analysis models. On this basis, MCNPX models are then applied for optimized calculations of the fast neutron flux at the RPV or at any other location of interest including e.g. at surveillance dosimeters. In that framework, the validation studies conducted so far have included one dosimeter set irradiated in a BWR/6 reactor during two relatively recent operating cycles. Although this first analysis revealed a satisfactory performance when comparing the calculation results to measured data, it was considered necessary to proceed with further sensitivity/optimization studies combined with an enlarged validation basis (i.e. using additional dosimeter sets) in order to strengthen the overall confidence in the scheme both at the qualitative and quantitative level. A summary of the recent progress achieved in these directions is presented in this paper. To start, recalling that BWRs are characterized by very complex and heterogeneous fuel assembly and core designs (e.g. pins with different enrichments and burnable absorber loading, partial length rods, fuel assemblies of different types in the core), the impact of such heterogeneities on FNF estimations is under investigation in order to determine the level of modeling details required for accurate computational schemes to be used for long-term evaluations of modern BWR core designs. Next, additional validation studies based on experimental dosimeter data obtained from the same BWR/6 reactor are presented. These enlarged validation studies involve the analysis of four dosimeter sets, each irradiated during one cycle (including the 3 first reactor operation cycles), and subsequently analyzed at the PSI Hot Lab shortly after the dosimeters extraction. All these additional validation studies are conducted using both the JEFF-3.1.1 and the ENDF/B-VII.0 continuous-energy neutron data libraries in order to assess the sensitivity of the PSI BWR computational scheme also upon the employed nuclear data.

The quantification of uncertainties of various calculation results, caused by the uncertainties associated with the input nuclear data, is a common task in nuclear reactor physics applications. Modern computation resources and improved knowledge on nuclear data allow nowadays to significantly advance the capabilities for practical investigations. Stochastic sampling is the method which has received recently a high momentum for its use and exploration in the domain of reactor design and safety analysis. An application of a stochastic sampling based tool towards nuclear reactor dosimetry studies is considered in the given paper with certain exemplary test evaluations. The stochastic sampling not only allows the input nuclear data uncertainties propagation through the calculations, but also an associated correlation analysis performance with no additional computation costs and for any parameters of interest can be done. Thus, an example of assessment of the Pearson correlation coefficients for several models, used in practical validation studies, is shown here. As a next step, the analysis of the obtained information is proposed for discussion, with focus on the systems similarities assessment. The benefits of the employed method and tools with respect to practical reactor dosimetry studies are consequently outlined.

At the Paul Scherrer Institute (PSI), a methodology titled PSI-NUSS is under development for the propagation of nuclear data uncertainties into Criticality Safety Evaluation (CSE) with the Monte Carlo code MCNPX. The primary purpose is to provide a complementary option for the uncertainty assessment related to nuclear data, versus the traditional approach which relies on estimating biases/uncertainties based on validation studies against representative critical benchmark experiments. In the present paper, the PSI-NUSS methodology is applied to quantify nuclear data uncertainties for the OECD/NEA UACSA Exercise Phase I benchmark. One underlying reason is that PSI's CSE methodology developed so far and previously applied for this benchmark was based on using a more conventional approach, involving engineering guesses in order to estimate uncertainties in the calculated effective multiplication factor (k(eff)). Therefore, as the PSI-NUSS methodology aims precisely at integrating a more rigorous treatment of the specific type of uncertainties from nuclear data for CSE, its application to the UACSA is conducted here: nuclear data related uncertainty component is estimated and compared to results obtained by other participants using different codes/libraries and methodologies.

This paper presents a study of the impact of the nuclear data (cross sections, neutron emission and spectra) on different quantities for spent nuclear fuels (SNF) from Swiss power plants: activities, decay heat, neutron and gamma sources and isotopic vectors. Realistic irradiation histories are considered using validated core follow-up models based on CASMO and SIMULATE. Two Pressurized and one Boiling Water Reactors (PWR and BWR) are considered over a large number of operated cycles. All the assemblies at the end of the cycles are studied, being reloaded or finally discharged, allowing spanning over a large range of exposure (from 4 to 60 MWd/kgU for ≃9200 assembly-cycles). Both UO2 and MOX fuels were used during the reactor cycles, with enrichments from 1.9 to 4.7% for the UO2 and 2.2 to 5.8% Pu for the MOX. The SNF characteristics presented in this paper are calculated with the SNF code. The calculated uncertainties, based on the ENDF/B-VII.1 library are obtained using a simple Monte Carlo sampling method. It is demonstrated that the impact of nuclear data is relatively important (e.g. up to 17% for the decay heat), showing the necessity to consider them for safety analysis of the SNF handling and disposal.

The newest release of the Evaluated Nuclear Data File, ENDF/B-VII.0, has recently become available, along with the announcement of its significant advances over previous versions. The older ENDF/B releases, however, have been assessed for numerous applications in the past and, as such, currently find wide application in the nuclear industry. An analysis of the influence of the recent upgrade in the data file is thus needed with respect to specific practical applications. The present technical note addresses the effects of modifications of the neutron cross-sections in the ENDF/B-VII.0 library, relative to the preceding ENDF/B-VI.8 release, on calculations of the fast neutron fluence accumulated in a PWR reactor pressure vessel, which is of direct relevance for the licensing and safe operation of nuclear power plants.[All rights reserved Elsevier].

This paper addresses the assessment of MCNPX-2.5.0 criticality calculations using continuous-energy neutron cross-section libraries based on ENDF/B-VI.8, JEF-2.2, JENDL-3.3, and the recently released ENDF/B-VII.0 and JEFF-3.1 data files. For this purpose, validation calculations were performed for a suite of benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. The benchmarks were selected on the basis of their similarity to designs found in today’s Light Water Reactor (LWR) compact storage pools and transport casks and in total comprised as much as 122 cases belonging to the category of thermal compound systems with low-enriched uranium. In order to define the ranges of applicability of the used calculational methods and to detect possible trends, the spectrum-related characteristics of the modeled critical experimental configurations were analysed. It is found that the latest ENDF/B-VII.0 and JEFF-3.1 libraries improve the older ENDF/B-VI.8 and JEF-2.2 compilations significantly and both lead to values for the weighted average of the normalized eigenvalues 〈 k eff calc / k eff exp 〉 very close to unity. All libraries have in common that any evidence of a statistically significant trend in the normalized eigenvalues versus both spectrum-related characteristics and experimental design parameters could not be found.

Studies in support of the assessment of aging structural materials in pressurized water reactors are being performed at the Paul Scherrer Institut. To that aim, a state-of-the-art methodology based on applying a CASMO-4/SIMULATE-3/MCNPX calculation scheme has been developed. In the frame of the methodology validation, an investigation is currently reported pertaining to the sensitivity of the calculated results, for a specific reactor pressure vessel scraping test, to the nuclear data used with the Monte Carlo code. Thus, the MCNPX-2.4.0 calculations have been carried out using three different data libraries, based on JEF-2.2, ENDF/B-VI.8 and JENDL-3.3 evaluations, respectively.A significant discrepancy ( 10%) in fast neutron flux (E1MeV) estimations has been observed between the results obtained with JENDL-3.3, versus the two other libraries, while noting that the later both provide very satisfactory agreement (within 5%) with the reference results based on the experimental data. Subsequent analysis has indicated that the observed discrepancy can be attributed mostly to differences in the oxygen data. The discussed cross-section differences could potentially lead to more sizable discrepancies for other applications, and thus need to be brought to the attention of neutron data evaluators and users.[All rights reserved Elsevier].

Capabilities for uncertainty quantification (UQ) with respect to nuclear data have been developed at PSI in the recent years and applied to the UAM benchmark. The guiding principle for the PSI UQ development has been to implement nonintrusive “black box” UQ techniques in state-of-the-art, production-quality codes used already for routine analyses. Two complimentary UQ techniques have been developed thus far: (i) direct perturbation (DP) and (ii) stochastic sampling (SS). The DP technique is, first and foremost, a robust and versatile sensitivity coefficient calculation, applicable to all types of input and output. Using standard uncertainty propagation, the sensitivity coefficients are folded with variance/covariance matrices (VCMs) leading to a local first-order UQ method. The complementary SS technique samples uncertain inputs according to their joint probability distributions and provides a global, all-order UQ method. This paper describes both DP and SS implemented in the lattice physics code CASMO-5MX (a special PSI-modified version of CASMO-5M) and a preliminary SS technique implemented in MCNPX, routinely used in criticality safety and fluence analyses. Results are presented for the UAM benchmark exercises I-1 (cell) and I-2 (assembly).

The disagreement of calculational results on the fast neutron flux at the pressure vessel of a pressurized water reactor obtained with modern neutron data libraries based on ENDF/B-VI.8, JEF-2.2 and JENDL-3.3 evaluations and using MCNPX Monte Carlo neutron transport code is analysed. Comparison of the neutron cross sections data important for the considered study and taken from these libraries has indicated that the observed results disagreement could be explained by differences in the 16 O(n,α) data and this is examined and discussed in the paper. The major conclusion of the given study is that presently the uncertainties in the 16 O(n,α) data could be considered as an important contribution to the overall fast neutron fluence calculational uncertainty.

The reactivity loss of PWR fuel with burnup has been investigated experimentally by measuring the reactivity worths of highly-burnt fuel samples in a PWR test lattice in the framework of the LWR-PROTEUS Phase II program. Seven UO2 samples cut from fuel rods irradiated in a Swiss PWR plant with burnups ranging up to ∼ 120 MWd/kg and four MOX samples with burnups up to ∼ 70 MWd/kg were inserted and withdrawn repeatedly in a test region constituted of actual PWR UO2 fuel rods in the center of the PROTEUS zero-power experimental facility. The measurements were analyzed using the CASMO-5 fuel assembly code and a cross-section library based on the ENDF/B-VII release 1 evaluation for the calculation of both the isotopic inventories of the samples and the reactivity effects in a model of the central PWR test region. The effects of nuclear data uncertainties on the calculated reactivity worths were quantified by using stochastic sampling of the data. The results show close proximity between calculated and measured reactivity effects, the overall mean of the calculated-to-experimental (C/E) ratio amounting to 0.978 with a standard deviation of 0.032. Moreover, the quality of the prediction remains at the same level throughout the very wide range of burnups of the investigated samples. The analysis thus demonstrates the high accuracy of the calculation of the reactivity of highly-burnt fuel.