| 1. |
- Plompen, A. J. M., et al.
(författare)
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The joint evaluated fission and fusion nuclear data library, JEFF-3.3
- 2020
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Ingår i: European Physical Journal A. - : Springer Science and Business Media LLC. - 1434-6001 .- 1434-601X. ; 56:7
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Forskningsöversikt (refereegranskat)abstract
- The joint evaluated fission and fusion nuclear data library 3.3 is described. New evaluations for neutron-induced interactions with the major actinides 235U, 238U and 239Pu, on 241Am and 23Na, 59Ni, Cr, Cu, Zr, Cd, Hf, W, Au, Pb and Bi are presented. It includes new fission yields, prompt fission neutron spectra and average number of neutrons per fission. In addition, new data for radioactive decay, thermal neutron scattering, gamma-ray emission, neutron activation, delayed neutrons and displacement damage are presented. JEFF-3.3 was complemented by files from the TENDL project. The libraries for photon, proton, deuteron, triton, helion and alpha-particle induced reactions are from TENDL-2017. The demands for uncertainty quantification in modeling led to many new covariance data for the evaluations. A comparison between results from model calculations using the JEFF-3.3 library and those from benchmark experiments for criticality, delayed neutron yields, shielding and decay heat, reveals that JEFF-3.3 performes very well for a wide range of nuclear technology applications, in particular nuclear energy.
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| 2. |
- Rochman, Dimitri, et al.
(författare)
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The TENDL library : Hope, reality and future
- 2017
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Ingår i: Nd 2016 Bruges. - Les Ulis : EDP Sciences. - 9782759890200
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
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| 4. |
- Koning, Arjan, et al.
(författare)
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TENDL : Complete Nuclear Data Library for Innovative Nuclear Science and Technology
- 2019
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Ingår i: Nuclear Data Sheets. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0090-3752 .- 1095-9904. ; 155, s. 1-55
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 5. |
- Rochman, Dimitri, et al.
(författare)
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Efficient use of Monte Carlo : Uncertainty Propagation
- 2014
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Ingår i: Nuclear science and engineering. - 0029-5639 .- 1943-748X. ; 177:3, s. 337-349
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Tidskriftsartikel (refereegranskat)abstract
- A new and faster Total Monte Carlo method for the propagation of nuclear data uncertaintiesin Monte Carlo nuclear simulations is presented (the fast TMC method).It is addressing the main drawback of the original Total Monte Carlo method(TMC), namely the necessary large time multiplication factor compared to a singlecalculation. With this new method, Monte Carlo simulations can now be accompaniedwith uncertainty propagation (other than statistical), with small additionalcalculation time. The fast TMC method is presented and compared with the TMCand fast GRS methods for criticality and shielding benchmarks and burn-up calculations.Finally, to demonstrate the efficiency of the method, uncertainties on localdeposited power in 12.7 millions cells are calculated for a full size reactor core,
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| 6. |
- Rochman, D., et al.
(författare)
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Nuclear Data Uncertainties for Typical LWR Fuel Assemblies and a Simple Reactor Core
- 2017
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Ingår i: Nuclear Data Sheets. - : Elsevier BV. - 0090-3752 .- 1095-9904. ; 139, s. 1-76
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Tidskriftsartikel (refereegranskat)abstract
- Abstract 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.
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| 7. |
- Rochman, D., et al.
(författare)
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Nuclear data uncertainty for criticality-safety : Monte Carlo vs. linear perturbation
- 2016
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Ingår i: Annals of Nuclear Energy. - : Elsevier BV. - 0306-4549 .- 1873-2100. ; 92, s. 150-160
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 8. |
- Rochman, D., et al.
(författare)
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Uncertainty Propagation with Fast Monte Carlo Techniques
- 2014
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Ingår i: Nuclear Data Sheets. - : Elsevier BV. - 0090-3752 .- 1095-9904. ; 118, s. 367-369
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Tidskriftsartikel (refereegranskat)abstract
- Two new and faster Monte Carlo methods for the propagation of nuclear data uncertainties in Monte Carlo nuclear simulations are presented (the "Fast TMC" and "Fast GRS" methods). They are addressing the main drawback of the original Total Monte Carlo method (TMC), namely the necessary large time multiplication factor compared to a single calculation. With these new methods, Monte Carlo simulations can now be accompanied with uncertainty propagation (other than statistical), with small additional calculation time. The new methods are presented and compared with the TMC methods for criticality benchmarks.
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