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  • 1.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Duan, Junfeng
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Gustavsson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Nuclear Research and Consultancy Group.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Combining Total Monte Carlo and Benchmarks for Nuclear Data Uncertainty Propagation on a Lead Fast Reactor's Safety Parameters2014In: Nuclear Data Sheets, ISSN 0090-3752, E-ISSN 1095-9904, Vol. 118, p. 542-544Article in journal (Refereed)
    Abstract [en]

    Analyses are carried out to assess the impact of nuclear data uncertainties on some reactor safety parameters for the European Lead Cooled Training Reactor (ELECTRA) using the Total Monte Carlo method. A large number of Pu-239 random ENDF-format libraries, generated using the TALYS based system were processed into ACE format with NJOY99.336 code and used as input into the Serpent Monte Carlo code to obtain distribution in reactor safety parameters. The distribution in keff obtained was compared with the latest major nuclear data libraries – JEFF-3.1.2, ENDF/B-VII.1 and JENDL-4.0. A method is proposed for the selection of benchmarks for specific applications using the Total Monte Carlo approach based on a correlation observed between the keff of a given system and the benchmark. Finally, an accept/reject criteria was investigated based on chi squared values obtained using the Pu-239 Jezebel criticality benchmark. It was observed that nuclear data uncertainties were reduced considerably from 748 to 443 pcm.

  • 2.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Duan, Junfeng
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Gustavsson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Nuclear Research and Consultancy Group.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Uncertainty analysis of Lead cross sections on reactor safety for ELECTRA2016In: SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo, 2016, article id 02401Conference paper (Refereed)
    Abstract [en]

    The Total Monte Carlo (TMC) method was used in this study to assess the impact of Pb-206, 207 and 208 nucleardata uncertainties on k-eff , beta-eff, coolant temperature coefficient, the coolant void worth for the ELECTRA reactor. Relatively large uncertainties were observed in the k-eff and the coolant void worth for all the isotopes with significant contribution coming from Pb-208 nuclear data. The large Pb-208 nuclear data uncertainty observed was further investigated by studying the impact of partial channels on the k-eff and beta-eff. Various sections of ENDF file: elasticscattering (n,el), inelastic scattering (n,inl), neutron capture (n,gamma), (n,2n), resonance parameters and the angular distribution were varied randomly and distributions in k-eff and beta-eff obtained. The dominant contributions to the uncertainty in the k-eff from Pb-208 came from uncertainties in the resonance parameters; however, elastic scattering cross section and the angular distribution also had significant impact. The impact of nuclear data uncertainties on the beta-eff was observed to be small.

  • 3.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Arjan, J. Koning
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Dimitri, Rochman
    Nuclear Research and Consultancy Group.
    Uncertainty and correlation analysis of lead nuclear data on reactor parameters for the European Lead Cooled Training Reactor2015In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 75, p. 26-37Article in journal (Refereed)
    Abstract [en]

    The Total Monte Carlo (TMC) method was used in this study to assess the impact of Pb-204, 206, 207, 208 nuclear data uncertainties on reactor safety parameters for the ELECTRA reactor. Relatively large uncertainties were observed in the k-eff and the coolant void worth (CVW) for all isotopes except for Pb-204 with signicant contribution coming from Pb-208 nuclear data; the dominant eectcame from uncertainties in the resonance parameters; however, elastic scattering cross section and the angular distributions also had signicant impact. It was also observed that the k-eff distribution for Pb-206, 207, 208 deviates from a Gaussian distribution with tails in the high k-eff region. An uncertainty of 0.9% on the k-eff and 3.3% for the CVW due to lead nuclear data were obtained. As part of the work, cross section-reactor parameter correlations were also studied using a Monte Carlo sensitivity method. Strong correlations were observed between the k-eff and (n,el) cross section for all the lead isotopes. The correlation between the (n,inl) and the k-eff was also found to be signicant.

  • 4.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nuclear Research and Consultancy Group, Petten, The Netherlands.
    Rochman, D.
    Laboratory for Reactor Physics Systems Behaviour, Paul Scherrer Institut, Villigen, Switzerland.
    Benchmark selection methodology for reactor calculations and nuclear data uncertainty reduction2015In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100Article in journal (Refereed)
    Abstract [en]

    Criticality, reactor physics and shielding benchmarks are expected to play important roles in GEN-IV design, safety analysis and in the validation of analytical tools used to design these reactors. For existing reactor technology, benchmarks are used for validating computer codes and for testing nuclear data libraries. Given the large number of benchmarks available, selecting these benchmarks for specic applications can be rather tedious and difficult. Until recently, the selection process has been based usually on expert judgement which is dependent on the expertise and the experience of the user and there by introducing a user bias into the process. This approach is also not suitable for the Total Monte Carlo methodology which lays strong emphasis on automation, reproducibility and quality assurance. In this paper a method for selecting these benchmarks for reactor calculation and for nuclear data uncertainty reduction based on the Total Monte Carlo (TMC) method is presented. For reactor code validation purposes, similarities between a real reactor application and one or several benchmarks are quantied using a similarity index while the Pearson correlation coecient is used to select benchmarks for nuclear data uncertainty reduction. Also, a correlation based sensitivity method is used to identify the sensitivity of benchmarks to particular nuclear reactions. Based on the benchmark selection methodology, two approaches are presented for reducing nuclear data uncertainty using integral benchmark experiments as an additional constraint in the TMC method: a binary accept/reject and a method of assigning file weights using the likelihood function. Finally, the methods are applied to a full lead-cooled fast reactor core and a set of criticality benchmarks. Signicant reductions in Pu-239 and Pb-208 nuclear data uncertainties were obtained after implementing the two methods with some benchmarks.

  • 5.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Int Atom Energy Commiss IAEA, Nucl Data Sect, Vienna, Austria.
    Rochman, Dmitri
    Paul Scherrer Inst, CH-5232 Villigen, Switzerland.
    On the use of integral experiments for uncertainty reduction of reactor macroscopic parameters within the TMC methodology2016In: Progress in nuclear energy (New series), ISSN 0149-1970, E-ISSN 1878-4224, Vol. 88, p. 43-52Article in journal (Refereed)
    Abstract [en]

    The current nuclear data uncertainties observed in reactor safety parameters for some nuclides call for safety concerns especially with respect to the design of GEN-IV reactors and must therefore be reduced significantly. In this work, uncertainty reduction using criticality benchmark experiments within the Total Monte Carlo methodology is presented. Random nuclear data libraries generated are processed and used to analyze a set of criticality benchmarks. Since the calculated results for each random nuclear data used are different, an algorithm was used to select (or assign weights to) the libraries which give a good description of experimental data for the analyses of the benchmarks. The selected or weighted libraries were then used to analyze the ELECTRA reactor. By using random nuclear data libraries constrained with only differential experimental data as our prior, the uncertainties observed were further reduced by constraining the files with integral experimental data to obtain a posteriori uncertainties on the k(eff). Two approaches are presented and compared: a binary accept/reject and a method of assigning file weights based on the likelihood function. Significant reductions in (PU)-P-239 and Pb-208 nuclear data uncertainties in the k(eff) were observed after implementing the two methods with some criticality benchmarks for the ELELIRA reactor. (C) 2015 Elsevier Ltd. All rights reserved.

  • 6.
    Alhassan, Erwin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    J. Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Reducing A Priori 239Pu Nuclear Data Uncertainty In The Keff Using A Set Of Criticality Benchmarks With Different Nuclear Data Libraries2015Conference paper (Other academic)
    Abstract [en]

    In the Total Monte Carlo (TMC) method [1] developed at the Nuclear Research and Consultancy Group for nuclear data uncertainty propagation, model calculations are compared with differential experimental data and a specific a priori uncertainty is assigned to each model parameter. By varying the model parameters all together within model parameter uncertainties, a full covariance matrix is obtained with its off diagonal elements if desired [1]. In this way, differential experimental data serve as a constraint for the model parameters used in the TALYS nuclear reactions code for the production of random nuclear data files. These files are processed into usable formats and used in transport codes for reactor calculations and for uncertainty propagation to reactor macroscopic parameters of interest.

     

    Even though differential experimental data together with their uncertainties are included (implicitly) in the production of these random nuclear data files in the TMC method, wide spreads in parameter distributions have been observed, leading to large uncertainties in reactor parameters for some nuclides for the European Lead cooled Training Reactor [2]. Due to safety concerns and the development of GEN-IV reactors with their challenging technological goals, the present uncertainties should be reduced significantly if the benefits from advances in modelling and simulations are to be utilized fully [3]. In Ref.[4], a binary accept/reject approach and a more rigorous method of assigning file weights based on the likelihood function were proposed and presented for reducing nuclear data uncertainties using a set of integral benchmarks obtained from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP). These methods are depended on the reference nuclear data library used, the combined benchmark uncertainty and the relevance of each benchmark for reducing nuclear data uncertainties for a particular reactor system. Since each nuclear data library normally comes with its own nominal values and covariance matrices, reactor calculations and uncertainties computed with these libraries differ from library to library.

     

    In this work, we apply the binary accept/reject approach and the method of assigning file weights based on the likelihood function for reducing a priori 239Pu nuclear data uncertainties for the European Lead Cooled Training Reactor (ELECTRA) using a set of criticality benchmarks. Prior and posterior uncertainties computed for ELECTRA using ENDF/B-VII.1, JEFF-3.2 and JENDL-4.0 are compared after including experimental information from over 10 benchmarks.

    [1] A.J. Koning and D. Rochman, Modern Nuclear Data Evaluation with the TALYS Code System. Nuclear Data Sheets 113 (2012) 2841-2934.

     

    [2] E. Alhassan, H. Sjöstrand, P. Helgesson, A. J. Koning, M. Österlund, S. Pomp, D. Rochman, Uncertainty and correlation analysis of lead nuclear data on reactor parameters for the European Lead Cooled Training reactor (ELECTRA). Annals of Nuclear Energy 75 (2015) 26-37.

     

    [3] G. Palmiotti, M. Salvatores, G. Aliberti, H. Hiruta, R. McKnight, P. Oblozinsky, W. Yang, A global approach to the physics validation of simulation codes for future nuclear systems, Annals of Nuclear Energy 36 (3) (2009) 355-361.

     

    [4] E. Alhassan, H. Sjöstrand, J. Duan, P. Helgesson, S. Pomp, M. Österlund, D. Rochman, A.J. Koning, Selecting benchmarks for reactor calculations: In proc. PHYSOR 2014 - The Role of Reactor Physics toward a Sustainable Future, kyoto, Japan, Sep. 28 - 3 Oct. (2014).

  • 7.
    Bajpeyi, Awanish
    et al.
    Rajiv Gandhi Inst Petr Technol, Dept Phys, Jais, Amethi, India..
    Shukla, A.
    Rajiv Gandhi Inst Petr Technol, Dept Phys, Jais, Amethi, India..
    Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Phys & Nucl Data Evaluat, Vienna, Austria.
    Systematic Nuclear Structure and Nuclear Reaction Studies Relevant to p-process2018In: Acta Physica Polonica B, ISSN 0587-4254, E-ISSN 1509-5770, Vol. 49, no 1, p. 27-40Article in journal (Refereed)
    Abstract [en]

    The cross section and reaction rate of the proton and alpha capture reactions on Pd-102, Te-120, Xe-124,Xe-126, and Ba-130,Ba-132 have been calculated through TALYS in Hauser-Feshbach formalism using relativistic mean field densities. Nuclear structure studies have been also carried out for the nuclei under consideration. Results obtained in the present work for nuclear structure as well as nuclear reaction are in a fair agreement with the available experimental results.

  • 8.
    Helgesson, Petter
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nucl Res & Consultancy Grp NRG, Petten, Netherlands.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Arjan, J. Koning
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nucl Res & Consultancy Grp NRG, Petten, Netherlands.
    Rydén, Jesper
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
    Rochman, Dimitri
    PSI, Villigen, Switzerland.
    Alhassan, Erwin
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Combining Total Monte Carlo and Unified Monte Carlo: Bayesian nuclear data uncertainty quantification from auto-generated experimental covariances2017In: Progress in nuclear energy (New series), ISSN 0149-1970, E-ISSN 1878-4224, Vol. 96, p. 76-96Article in journal (Refereed)
    Abstract [en]

    The Total Monte Carlo methodology (TMC) for nuclear data (ND) uncertainty propagation has been subject to some critique because the nuclear reaction parameters are sampled from distributions which have not been rigorously determined from experimental data. In this study, it is thoroughly explained how TMC and Unified Monte Carlo-B (UMC-B) are combined to include experimental data in TMC. Random ND files are weighted with likelihood function values computed by comparing the ND files to experimental data, using experimental covariance matrices generated from information in the experimental database EXFOR and a set of simple rules. A proof that such weights give a consistent implementation of Bayes' theorem is provided. The impact of the weights is mainly studied for a set of integral systems/applications, e.g., a set of shielding fuel assemblies which shall prevent aging of the pressure vessels of the Swedish nuclear reactors Ringhals 3 and 4.

    In this implementation, the impact from the weighting is small for many of the applications. In some cases, this can be explained by the fact that the distributions used as priors are too narrow to be valid as such. Another possible explanation is that the integral systems are highly sensitive to resonance parameters, which effectively are not treated in this work. In other cases, only a very small number of files get significantly large weights, i.e., the region of interest is poorly resolved. This convergence issue can be due to the parameter distributions used as priors or model defects, for example.

    Further, some parameters used in the rules for the EXFOR interpretation have been varied. The observed impact from varying one parameter at a time is not very strong. This can partially be due to the general insensitivity to the weights seen for many applications, and there can be strong interaction effects. The automatic treatment of outliers has a quite large impact, however.

    To approach more justified ND uncertainties, the rules for the EXFOR interpretation shall be further discussed and developed, in particular the rules for rejecting outliers, and random ND files that are intended to describe prior distributions shall be generated. Further, model defects need to be treated.

  • 9.
    Helgesson, Petter
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    J. Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA.
    Rochman, Dimitri
    New 59Ni data including uncertainties and consequences for gas production in steel in LWR spectraNew 59Ni data including uncertainties and consequences for gas production in steel in LWR spectra2015Conference paper (Other academic)
    Abstract [en]

    Abstract: With ageing reactor fleets, the importance of estimating material damage parameters in structural materials is increasing. 59Ni is not naturally abundant, but as noted in, e.g., Ref. [1], the two-step reaction 58Ni(n,γ)59Ni(n,α)56Fe gives a very important contribution to the helium production and damage energy in stainless steel in thermal spectra, because of the extraordinarily large thermal (n,α) cross section for 59Ni (for most other nuclides, the (n,α) reaction has a threshold). None of the evaluated data libraries contain uncertainty information for (n,α) and (n,p) for 59Ni for thermal energies and the resonance region. Therefore, new such data is produced in this work, including random data to be used with the Total Monte Carlo methodology [2] for nuclear data uncertainty propagation.

                      The limited R-matrix format (“LRF = 7”) of ENDF-6 is used, with the Reich-Moore approximation (“LRF = 3” is just a subset of Reich-Moore). The neutron and gamma widths are obtained from TARES [2], with uncertainties, and are translated into LRF = 7. The α and proton widths are obtained from the little information available in EXFOR [3] (assuming large uncertainties because of lacking documentation) or from sampling from unresolved resonance parameters from TALYS [2], and they are split into different channels (different excited states of the recoiling nuclide, etc.). Finally, the cross sections are adjusted to match the experiments at thermal energies, with uncertainties.

                      The data is used to estimate the gas production rates for different systems, including the propagated nuclear data uncertainty. Preliminary results for SS304 in a typical thermal spectrum, show that including 59Ni at its peak concentration increases the helium production rate by a factor of 4.93 ± 0.28 including a 5.7 ± 0.2 % uncertainty due to the 59Ni data. It is however likely that the uncertainty will increase substantially from including the uncertainty of other nuclides and from re-evaluating the experimental thermal cross sections.

  • 10.
    Helgesson, Petter
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    J. Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA.
    Rochman, Dimitri
    Alhassan, Erwin
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Towards Transparent, Reproducible And Justified Nuclear Data Uncertainty Propagation For Lwr Applications2015Conference paper (Other academic)
    Abstract [en]

    Any calculated quantity is practically meaningless without estimates on the uncertainty of theobtained results, not the least when it comes to, e.g., safety parameters in a nuclear reactor. Oneof the sources of uncertainty in reactor physics computations or simulations are the uncertaintiesof the so called nuclear data, i.e., cross sections, angular distributions, fission yields, etc. Thecurrently dominating method for propagating nuclear data uncertainties (using covariance dataand sensitivity analysis) suffers from several limitations, not the least in how the the covariancedata is produced – the production relies to a large extent on personal judgment of nuclear dataevaluators, leading to results which are difficult to reproduce from fundamental principles.Further, such a method assumes linearity, it in practice limits both input and output to bemodeled as Gaussian distributions, and the covariance data in the established nuclear datalibraries is incomplete.“Total Monte Carlo” (TMC) is a nuclear data uncertainty propagation method based on randomsampling of nuclear reaction model parameters which aims to resolve these issues. The methodhas been applied to various applications, ranging from pin cells and criticality safety benchmarksto full core neutronics as well as models including thermo-hydraulics and transients. However,TMC has been subject to some critique since the distributions of the nuclear model parameters,and hence of the nuclear data, has not been deduced from really rigorous statistical theory. Thispresentation briefly discusses the ongoing work on how to use experimental data to approachjustified results from TMC, including the effects of correlations between experimental datapoints and the assessment of such correlations. In this study, the random nuclear data libraries areprovided with likelihood weights based on their agreement to the experimental data, as a meansto implement Bayes' theorem.Further, it is presented how TMC is applied to an MCNP-6 model of shielding fuel assemblies(SFA) at Ringhals 3 and 4. Since the damage from the fast neutron flux may limit the lifetimes ofthese reactors, parts of the fuel adjacent to the pressure vessel is replaced by steel (the SFA) toprotect the vessel, in particular the four points along the belt-line weld which have been exposedto the largest fluence over time. The 56Fe data uncertainties are considered, and the estimatedrelative uncertainty at a quarter of the pressure vessel is viewed in Figure 1 (right) as well as theflux pattern itself (left). The uncertainty in the flux reduction at a selected sensitive point is 2.5± 0.2 % (one standard deviation). Applying the likelihood weights does not have muchimpact for this case, which could indicate that the prior distribution for the 56Fe data is too“narrow” (the used libraries are not really intended to describe a prior distribution), and that thetrue uncertainty is substantially greater. Another explanation could be that the dominating sourceof uncertainty is the high-energy resonances which are treated inefficiently by such weights.In either case, the efforts to approach justified, transparent, reproducible and highly automatizednuclear data uncertainties shall continue. On top of using libraries that are intended to describeprior distributions and treating the resonance region appropriately, the experimental correlationsshould be better motivated and the treatment of outliers shall be improved. Finally, it is probablynecessary to use experimental data in a more direct sense where a lot of experimental data isavailable, since the nuclear models are imperfect.Figure 1. The high energy neutron flux at the reactor pressure vessel in the SFA model, and thecorresponding propagated 56Fe data uncertainty.

  • 11.
    Helgesson, Petter
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nuclear Research and Consultancy Group NRG, Petten, The Netherlands.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Paul Scherrer Institute PSI, Villigen, Switzerland.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA Nuclear Data Section, Vienna, Austria.
    Evaluation of the Ni-59 cross sections including thermal (n,alpha), (n,p) and complete uncertainty information2016Other (Other academic)
  • 12.
    Helgesson, Petter
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nuclear Research and Consultancy Group NRG, Petten, The Netherlands.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Paul Scherrer Institute PSI, Villigen, Switzerland.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA Nuclear Data Section, Vienna, Austria.
    Ni-59 cross section evaluation: covariance focus2016Other (Other academic)
  • 13.
    Koning, Arjan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, POB 100, A-1400 Vienna, Austria.
    Rochman, D.
    Paul Scherrer Inst, Lab Reactor Phys Syst Behav, Villigen, Switzerland.
    Sublet, J-Ch
    IAEA, Nucl Data Sect, POB 100, A-1400 Vienna, Austria.
    Dzysiuk, N.
    NRG, Westerduinweg 3, NL-1755 LE Petten, Netherlands;Taras Shevchenko Natl Univ Kyiv, Kiev, Ukraine.
    Fleming, M.
    OECD, Nucl Energy Agcy, F-92100 Boulogne, France;United Kingdom Atom Energy Author, Culham Sci Ctr, Abingdon OX14 3DB, Oxon, England.
    van der Marck, S.
    NRG, Westerduinweg 3, NL-1755 LE Petten, Netherlands.
    TENDL: Complete Nuclear Data Library for Innovative Nuclear Science and Technology2019In: Nuclear Data Sheets, ISSN 0090-3752, E-ISSN 1095-9904, Vol. 155, p. 1-55Article in journal (Refereed)
    Abstract [en]

    The TENDL library is now established as one of the major nuclear data libraries in the world, striving for completeness and quality of nuclear data files for all isotopes, evaluation methods, processing and applied performance. To reach this status, some basic principles have been applied which sets it apart from other libraries: reproducible dedicated evaluations when differential data are available, through determination of nuclear models implemented in TALYS and their parameters, completeness (with or without experimental data), format and processing standardization, automation of production and reproducibility. In this paper, we will outline how such an approach has become a reality, and recall some of the past successes since the first TENDL release in 2008. Next, we will demonstrate the performance of the latest TENDL releases for different application fields, as well as new approaches for uncertainty quantification based on Bayesian inference methods and possible differential and integral adjustments. Also, current limitations of the library performances due to modelling and needs for new and more precise experimental data will be outlined.

  • 14.
    Leray, Olivier
    et al.
    Paul Scherrer Inst, Villigen, Switzerland.
    Rochman, Dimitri
    Paul Scherrer Inst, Villigen, Switzerland.
    Fleming, Michael
    United Kingdom Atom Energy Author, Abingdon, Oxon, England.
    Sublet, Jean-Christophe
    United Kingdom Atom Energy Author, Abingdon, Oxon, England.
    Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, Vienna, Austria.
    Vasiliev, Alexander
    Paul Scherrer Inst, Villigen, Switzerland.
    Ferroukhi, Hakim
    Paul Scherrer Inst, Villigen, Switzerland.
    Fission yield covariances for JEFF: A Bayesian Monte Carlo method2017In: ND 2016: INTERNATIONAL CONFERENCE ON NUCLEAR DATA FOR SCIENCE AND TECHNOLOGY / [ed] Plompen, A Hambsch, FJ Schillebeeckx, P Mondelaers, W Heyse, J Kopecky, S Siegler, P Oberstedt, S, Les Ulis: EDP Sciences, 2017, article id 09023Conference paper (Refereed)
    Abstract [en]

    The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties) and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.

  • 15.
    Pomp, Stephan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Al-Adili, Ali
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Alhassan, Erwin
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Gustavsson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Hellesen, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Lantz, Mattias
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, D.
    Simutkin, V.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Solders, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Experiments and Theoretical Data for Studying the Impact of Fission Yield Uncertainties on the Nuclear Fuel Cycle with TALYS/GEF and the Total Monte Carlo Method2015In: Nuclear Data Sheets, ISSN 0090-3752, E-ISSN 1095-9904, Vol. 123, no SI, p. 220-224Article in journal (Refereed)
    Abstract [en]

    We describe the research program of the nuclear reactions research group at Uppsala University concerning experimental and theoretical efforts to quantify and reduce nuclear data uncertainties relevant for the nuclear fuel cycle. We briefly describe the Total Monte Carlo (TMC) methodology and how it can be used to study fuel cycle and accident scenarios, and summarize our relevant experimental activities. Input from the latter is to be used to guide the nuclear models and constrain parameter space for TMC. The TMC method relies on the availability of good nuclear models. For this we use the TALYS code which is currently being extended to include the GEF model for the fission channel. We present results from TALYS-1.6 using different versions of GEF with both default and randomized input parameters and compare calculations with experimental data for U-234(n,f) in the fast energy range. These preliminary studies reveal some systematic differences between experimental data and calculations but give overall good and promising results.

  • 16.
    Rochman, D.
    et al.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Goriely, S.
    Univ Libre Bruxelles, Inst Astron & Astrophys, CP 226, B-1050 Brussels, Belgium..
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, Vienna, Austria..
    Ferroukhi, H.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Radiative neutron capture: Hauser Feshbach vs. statistical resonances2017In: Physics Letters B, ISSN 0370-2693, E-ISSN 1873-2445, Vol. 764, p. 109-113Article in journal (Refereed)
    Abstract [en]

    The radiative neutron capture rates for isotopes of astrophysical interest are commonly calculated on the basis of the statistical Hauser Feshbach (HF) reaction model, leading to smooth and monotonically varying temperature-dependent Maxwellian-averaged cross sections (MACS). The HF approximation is known to be valid if the number of resonances in the compound system is relatively high. However, such a condition is hardly fulfilled for keV neutrons captured on light or exotic neutron-rich nuclei. For this reason, a different procedure is proposed here, based on the generation of statistical resonances. This novel technique, called the "High Fidelity Resonance" (HFR) method is shown to provide similar results as the HF approach for nuclei with a high level density but to deviate and be more realistic than HF predictions for light and neutron-rich nuclei or at relatively low sub-keV energies. The MACS derived with the HFR method are systematically compared with the traditional HF calculations for some 3300 neutron-rich nuclei and shown to give rise to significantly larger predictions with respect to the HF approach at energies of astrophysical relevance. For this reason, the HF approach should not be applied to light or neutron-rich nuclei. The Doppler broadening of the generated resonances is also studied and found to have a negligible impact on the calculated MACS.

  • 17.
    Rochman, D.
    et al.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Leray, O.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Perret, G.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Vasiliev, A.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Ferroukhi, H.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, A-1400 Vienna, Austria..
    Re-evaluation of the thermal neutron capture cross section of Nd-1472016In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 94, p. 612-617Article in journal (Refereed)
    Abstract [en]

    In this paper we are proposing a re-evaluation of the thermal-neutron induced capture cross section of Nd-147. A unique measurement exists from which this cross section was calculated in 1974. This original calculation is based on an assumed value for a specific gamma-ray fraction (called F-2), taken from the neighboring nucleus Nd-145. With the availability of reaction codes such as TALYS, such fraction can nowadays be calculated using specific reaction models and parameters. The new value of F-2 indicates a decrease of the thermal cross section by 45%, leading to 243 barns, instead of the 440 barns previously reported. This new cross section impacts the calculation of the number density for the well-known burn-up indicator Nd-148, but as shown, the change is close to the usual experimental uncertainties for the 148Nd number densities, thus having a limited impact on burn-up calculation.

  • 18.
    Rochman, D.
    et al.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Leray, O.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Vasiliev, A.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Ferroukhi, H.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, Vienna, Austria..
    Fleming, M.
    Culham Ctr Fus Energy, Abingdon, Oxon, England..
    Sublet, J. C.
    Culham Ctr Fus Energy, Abingdon, Oxon, England..
    A Bayesian Monte Carlo method for fission yield covariance information2016In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 95, p. 125-134Article in journal (Refereed)
    Abstract [en]

    The present work proposes a Bayesian method to combine theoretical fission yields with a set of reference data. These two sources of information are merged using a Monte Carlo process, and leads to a so-called Bayesian Monte Carlo update. Examples are presented for the independent fission yields of four major actinides, using the GEF code as a source of theoretical calculations and an evaluated library of fission yields for the reference data. The impact of the updated fission yields and their covariances is shown for two distinct applications: a UO2 pincell with burn-up up to 40 GWD/tHM and decay heat calculations of a thermal neutron pulse on U-235 and Pu-239.

  • 19.
    Rochman, D.
    et al.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Vasiliev, A.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Ferroukhi, H.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
    Zhu, T.
    Univ Florida, Gainesville, FL USA..
    van der Marck, S. C.
    Nucl Res & Consultancy Grp NRG, Petten, Netherlands..
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, A-1400 Vienna, Austria.
    Nuclear data uncertainty for criticality-safety: Monte Carlo vs. linear perturbation2016In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 92, p. 150-160Article in journal (Refereed)
    Abstract [en]

    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 key 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.

  • 20.
    Rochman, Dimitri
    et al.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. IAEA, Nucl Data Sect, Vienna, Austria.
    Sublet, J.Ch.
    United Kingdom Atom Energy Author, Abingdon, Oxon, England.
    Fleming, M.
    United Kingdom Atom Energy Author, Abingdon, Oxon, England.
    Bauge, E.
    CEA, DAM, DIF, Serv Phys Nucl, Gif Sur Yvette, France.
    S., Hilaire
    CEA, DAM, DIF, Serv Phys Nucl, Gif Sur Yvette, France.
    Romain, P.
    CEA, DAM, DIF, Serv Phys Nucl, Gif Sur Yvette, France.
    Morillon, B.
    CEA, DAM, DIF, Serv Phys Nucl, Gif Sur Yvette, France.
    Duarte, H.
    CEA, DAM, DIF, Serv Phys Nucl, Gif Sur Yvette, France.
    Goriely, S.
    Univ Libre Bruxelles, B-1050 Brussels, Belgium.
    van der Marck, S.C.
    NRG, Petten, Netherlands.
    Sjöstrand, Henrik
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Dzysiuk, N.
    NRG, Petten, Netherlands.
    Cabellos, O.
    OECD Nucl Energy Agcy, Paris, France.
    Ferroukhi, H.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland.
    Vasiliev, A.
    Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland.
    The TENDL library: Hope, reality and future2017In: Nd 2016 Bruges: International Conference On Nuclear Data For Science And Technology / [ed] Plompen, A.; Hambsch, FJ.; Schillebeeckx, P.; Mondelaers, W.; Heyse, J.; Kopecky, S.; Siegler, P.; Oberstedt, S., Les Ulis: EDP Sciences, 2017, Vol. 146, article id 02006Conference paper (Refereed)
    Abstract [en]

    The TALYS Evaluated Nuclear Data Library (TENDL) has now 8 releases since 2008. Considerable experience has been acquired for the production of such general-purpose nuclear data library based on the feedback from users, evaluators and processing experts. The backbone of this achievement is simple and robust: completeness, quality and reproducibility. If TENDL is extensively used in many fields of applications, it is necessary to understand its strong points and remaining weaknesses. Alternatively, the essential knowledge is not the TENDL library itself, but rather the necessary method and tools, making the library a side product and focusing the efforts on the evaluation knowledge. The future of such approach will be discussed with the hope of nearby greater success.

  • 21.
    Sjöstrand, Henrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Alhassan, Erwin
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Conroy, Sean
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Duan, Junfeng
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Hellesen, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Arjan, Koning J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Dimitri, Rochman
    Nuclear Research and Consultancy Group.
    Total Monte Carlo evaluation for dose calculations2014In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 161, no 1-4, p. 312-315Article in journal (Refereed)
    Abstract [en]

    Total Monte Carlo (TMC) is a method to propagate nuclear data (ND) uncertainties in transport codes, by using a large set of ND files, which covers the ND uncertainty. The transport code is run multiple times, each time with a unique ND file, and the result is a distribution of the investigated parameter, e.g. dose, where the width of the distribution is interpreted as the uncertainty due to ND. Until recently, this was computer intensive, but with a new development, fast TMC, more applications are accessible. The aim of this work is to test the fast TMC methodology on a dosimetry application and to propagate the 56Fe uncertainties on the predictions of the dose outside a proposed 14-MeV neutron facility. The uncertainty was found to be 4.2 %. This can be considered small; however, this cannot be generalised to all dosimetry applications and so ND uncertainties should routinely be included in most dosimetry modelling.

  • 22.
    Sjöstrand, Henrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Alhassan, Erwin
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Duan, Junfeng
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Gustavsson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Nuclear Research and Consultancy Group.
    Österlund, Michael
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Propagation of nuclear data uncertainties for ELECTRA burn-up calculations2014In: Nuclear Data Sheets, ISSN 0090-3752, E-ISSN 1095-9904, Vol. 118, p. 527-530Article in journal (Refereed)
    Abstract [en]

    The European Lead-Cooled Training Reactor (ELECTRA) has been proposed as a training reactor for fast systems within the Swedish nuclear program. It is a low -power fast reactor cooled by pure liquid lead. In this work, we propagate the uncertainties in 239Pu transport data to uncertainties in the fuel inventory of ELECTRA during the reactor life using the Total Monte Carlo approach(TMC). Within the TENDL project the nuclear models input parameters were randomized within their uncertainties and 740 239Pu nuclear data libraries were generated. These libraries are used as inputs to reactor codes, in our case SERPENT, to perform uncertainty analysis of nuclear reactor inventory during burn-up. The uncertainty in the inventory determines uncertainties in: the long term radio-toxicity, the decay heat, the evolution of reactivity parameters, gas pressure and volatile fission product content. In this work, a methodology called fast TMC is utilized, which reduces the overall calculation time. The uncertainty in the long-term radiotoxicity, decay heat, gas pressureand volatile fission products were found to be insignificant. However, the uncertainty of some minor actinides were observed to be rather large and therefore their impact on multiple recycling should be investigated further. It was also found that, criticality benchmarks can be used to reduce inventory uncertainties due to nuclear data. Further studies are needed to include fission yield uncertainties, more isotopes, and a larger set of benchmarks.

  • 23.
    Sjöstrand, Henrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Conroy, Sean
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Helgesson, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Hernandez Solis, Augusto
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Koning, Arjan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. Nuclear Data Section, IAEA, Vienna, Austria.
    Pomp, Stephan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
    Rochman, Dimitri
    Reactor Physics and Systems Behaviour Laboratory, Paul Scherrer Institut, Villigen, Switzerland.
    Propagation of nuclear data uncertainties for fusion power measurements2017In: ND 2016: International Conference On Nuclear Data For Science And Technology / [ed] Plompen, A.; Hambsch, FJ.; Schillebeeckx, P.; Mondelaers, W.; Heyse, J.; Kopecky, S.; Siegler, P.; Oberstedt, S., Les Ulis: EDP Sciences, 2017, Vol. 146, no 02034, article id 02034Conference paper (Refereed)
    Abstract [en]

    Neutron measurements using neutron activation systems are an essential part of the diagnostic system at large fusion machines such as JET and ITER. Nuclear data is used to infer the neutron yield. Consequently, high-quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are not fully taken into account in uncertainty analysis for neutron yield calibrations using activation foils. This paper investigates the neutron yield uncertainty due to nuclear data using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of the JET fusion machine; the uncertainties due to the cross-sections and angular distributions in JET structural materials, as well as the activation cross-sections in the activation foils, are analysed. It is found that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.

1 - 23 of 23
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