1. Modern nuclear data evaluation: straight from nuclear physics to applications Arjan Koning NRG Petten, the Netherlands April 23 2010, CIAE, Beijing

2. 2 Acknowledgements NRG Petten: Dimitri Rochman, Marieke Duijvestijn CEA-Bruyeres-le-Chatel: Stephane Hilaire, Eric Bauge, Pascal Romain Univ. Libre Bruxelles: Stephane Goriely CEA Saclay: Jacques Raynal IRMM Geel: Arjan Plompen IAEA: Roberto Capote JUKO research: Jura Kopecky KIT: Alexander Konobeyev Many TALYS users for forcing us to improve the code.

3. 3 Contents Introduction: A new way of nuclear data evaluation Essence of software development and reproducibility -Example: TALYS code system Implications and possibilities: -Large scale nuclear data library production (TENDL) -Monte Carlo uncertainty propagation -Automatic validation and optimization with integral measurements Conclusions

4. 4 Objective There are limits in our knowledge of nuclear physics: Experimental possibilities and precision Theoretical nuclear structure and reaction models which requires and deserves everlasting support Mantra: let’s at least provide all nuclear physics knowledge we know up to now in a form ready for applications, while maximizing Completeness: no unnecessary omissions Quality: no unnecessary approximations but with a quantitative measure about our knowledge (uncertainty information)

5. 5 Nuclear data libraries: up to now During one nuclear data generation: Evaluators make, and later correct, mistakes Evaluators improve their methods (more complete ENDF-6 files, covariances) New experimental data and better nuclear model codes emerge Up to now, such progress has not been consistently implemented in isotopic data libraries. E.g. : 96-Cm-247 JAERI-ORNL EVAL-OCT05 R.Q. Wright, T.Nakagawa, T.Liu 96-Cm-248 HEDL,SRL,+ EVAL-APR78 Mann,Benjamin,Howerton, + 96-Cm-249 JAERI EVAL-OCT95 T.Nakagawa and T.Liu 96-Cm-250 JAERI EVAL-OCT95 T.Nakagawa and T.Liu 27-Co- 58 NEA RCOM-JUN83 Scientific Co-ordinating Group 27-Co- 58MNEA RCOM-JUN82 Scientific Co-ordination Group 27-Co- 59 ANL,ORNL EVAL-JUL89 A.Smith+,G.Desaussure+ 24-Cr- 50 LANL,ORNL EVAL-OCT97 S.Chiba,M.Chadwick,D.Hetrick

6. 6 Nuclear data libraries: another way Nuclear data knowledge should no longer be assembled in an ENDF-6 nuclear data library, but one level deeper: Resonance parameters + uncertainties An error-free EXFOR database Nuclear models: -A robust, validated, multipurpose nuclear model code -A Reference Parameter Input Library (RIPL) -For important/measured nuclides: A set of adjusted model parameters + uncertainties If needed: per nuclide a script with other actions (copying parts of other libraries, direct inclusion of experiment, etc.) Store the above, and make sure that ENDF formatting, processing and integral validation become “trivial” This yields entirely new possibilities

7. 7 Resonance Parameters. TARES Experimental data (EXFOR) Nucl. model parameters TALYS TEFAL Output ENDF Gen. purpose file ENDF/EAF Activ. file NJOY PROC. CODE MCNP FIS- PACT Nuclear data scheme + covariances -K-eff -Neutron flux -Etc. -activation - transmutation Determ. code Other (ORIGEN) +Uncertainties +Covariances +(Co)variances +Covariances TASMAN Monte Carlo: 1000 TALYS runs

8. 8 Loop over energies and isotopes PRE-EQUILIBRIUM Exciton model Partial densities Kalbach systematic Approx DSD Angular distributions Cluster emissions  emission Exciton model Hauser-Feshbach Fission  cascade Exclusive channels Recoils MULTIPLE EMISSIONSTRUCTURE Abundances Discrete levels Deformations Masses Level densities Resonances Fission parameters Radial matter dens. OPTICAL MODEL Phenomenologic Local or global Semi-Microscopic Tabulated (ECIS) DIRECT REACTION Spherical / DWBA Deformed / Coupled channel Giant Resonances Pickup, stripping, exchange Rotational Vibrational COMPOUND Hauser-Feshbach Fluctuations Fission  Emission Level densities GC + Ignatyuk Tabulated Superfluid Model INPUT projectile n element Fe mass 56 energy 0.1. TALYS code scheme OUTPUT Spectra XS Fission yields DDX Etc. How ? 11/09/2007 - FINUSTAR 2 6/20

9. 9 TALYS-1.2 Released December 21, 2009, see www.talys.eu Use of TALYS still increasing -Estimated 400-500 users, 160-200 publications Some recent improvements for TALYS-1.2: -Better fission + level density model (CEA Bruyeres-le- Chatel) -The option to easily/safely store the best input parameter set per nucleus (“best y”) -More flexibility for covariance development and adjustment to experimental data TALYS can be used for -In-depth nuclide/reaction analyses -Global multi-nuclide calculations -These two are now being merged

10. 10 Resonance Parameters. TARES Experimental data (EXFOR) Nucl. model parameters TALYS TEFAL Output ENDF Gen. purpose file ENDF/EAF Activ. file NJOY PROC. CODE MCNP FIS- PACT Nuclear data scheme + covariances -K-eff -Neutron flux -Etc. -activation - transmutation Determ. code Other (ORIGEN) +Uncertainties +Covariances +(Co)variances +Covariances TASMAN Monte Carlo: 1000 TALYS runs

11. 11 Uncertainties with Monte Carlo Standard procedure: Determine uncertainty range for each nuclear model parameter Do a first TALYS calculation (“run 0”) with central values Perform K(=1000) TALYS calculations with all parameters random Covariance matrix for cross sections i and j: Various refinements possible: -Reject outlying results (leads to parameter correlations) -More precise inclusion of experimental data (Unified MC, D. Smith, H. Leeb), backward-forward MC (E. Bauge), etc.

12. 12 Uncertainties for Cu isotopes

13. 13

14. 14 Resonance Parameters. TARES Experimental data (EXFOR) Nucl. model parameters TALYS TEFAL Output ENDF Gen. purpose file ENDF/EAF Activ. file NJOY PROC. CODE MCNP FIS- PACT Nuclear data scheme + covariances -K-eff -Neutron flux -Etc. -activation - transmutation Determ. code Other (ORIGEN) +Uncertainties +Covariances +(Co)variances +Covariances TASMAN Monte Carlo: 1000 TALYS runs

15. 15 Application 1: TENDL TALYS Evaluated Nuclear Data Library, www.talys.eu/tendl2009 n, p, d, t,h, a and g libraries in ENDF-6 format 2400 nuclides (all with lifetime > 1 sec.) up to 200 MeV Neutrons: complete covariance data (MF31-MF35) MCNP-libraries (n,p and d) and multi-group covariances (n only) Production time: 2 months (40 processors) Strategy: Always ensure completeness, global improvement in 2010, 2011.. Extra effort for important nuclides, especially when high precision is required (e.g. actinides): adjusted parameters (data fitting). These input files per nuclide are stored for future use. All libraries are always reproducible from scratch The ENDF-6 libraries are created, not manually touched

16. 16 TENDL users European Activation File (EAF): > 95% TALYS/TENDL based Fusion Evaluated Nuclear Data Library (FENDL) -Missing nuclides, high energies, covariances, protons and deuterons Joint Evaluated Fission and Fusion file (JEFF) -Missing nuclides (JEFF-3.2), protons and deuterons NEA Data Bank: Janis (E. Dupont, N. Soppera) IAEA: visualisation system (V. Zerkin) Fusion/IFMIF research (Sanz, Sauvan): protons and deuterons Many downloads from www.talys.eu/tendl2009 So far, TENDL is adopted “when nothing else exists”, but a lot of effort has been devoted to nuclide-by-nuclide neutron evaluations. We can be more ambitious!

17. 17 TENDL: Complete ENDF-6 data libraries MF1: description and average fission quantities MF2: resonance data MF3: cross sections MF4: angular distributions MF5: energy spectra MF6: double-differential spectra, particle yields and residual products MF8-10: isomeric cross sections and ratios MF12-15: gamma yields, spectra and angular distributions MF31: covariances of average fission quantities (TENDL-2010) MF32: covariances of resonance parameters MF33: covariances of cross sections MF34: covariances of angular distributions MF35: covariances of fission neutron spectra (TENDL-2010) and particle spectra (TENDL-2011) MF40: covariances of isomeric data (TENDL-2011)

18. 18 IAEA covariance visualisation system (V. Zerkin)

19. 19

20. 20

21. 21

22. 22

23. 23 Quality of proton data (MCNPX, A. Konobeyev, KIT) ENDF/B-VII-p (LA-150): 30-40 nuclides TENDL-2009: 1170 nuclides (Chi-2) ( ) (H x F)

24. 24 Application 2: “Total” Monte Carlo Propagating covariance data is an approximation of true uncertainty propagation (especially regarding ENDF-6 format limitations) Covariance data requires extra processing and “satellite software” for application codes Alternative: Create an ENDF-6 file for each random sample and finish the entire physics-to-application loop.

25. 25 Resonance Parameters. TARES Experimental data (EXFOR) Nucl. model parameters TALYS TEFAL Output ENDF Gen. purpose file ENDF/EAF Activ. file NJOY PROC. CODE MCNP FIS- PACT Nuclear data scheme + covariances -K-eff -Neutron flux -Etc. -activation - transmutation Determ. code Other (ORIGEN) +Uncertainties +Covariances +(Co)variances +Covariances TASMAN Monte Carlo: 1000 TALYS runs

26. 26 Resonance Parameters. TARES Experimental data (EXFOR) Nucl. model parameters TALYS TEFAL Output ENDF Gen. purpose file ENDF/EAF Activ. file NJOY PROC. CODE MCNP FIS- PACT Nuclear data scheme: Total Monte Carlo -K-eff -Neutron flux -Etc. - activation - transmutation Determ. code Other codes +Uncertainties +Covariances TASMAN Monte Carlo: 1000 runs of all codes

27. 27

28. 28

29. 29

30. 30

31. 31

32. 32

33. 33

34. 34

35. 35

36. 36

37. 37

38. 38

39. 39

40. 40

41. 41

42. 42

43. 43

44. 44

45. 45

46. 46

47. 47

48. 48

49. 49

50. 50 Total Monte Carlo versus covariances Advantages:Advantages: - Relatively quick- Exact - Use in sensitivity study- Requires only “main” software - Easier release (TENDL) Disadvantages:Disadvantages: - Approximative (cross-correlations)- (Computer) time consuming - No covariance for gamma production,- Backward (sensitivity) route DDX, etc. not obvious - Requires special processing - Requires covariance software for application codes

51. 51 Application: criticality benchmarks Total of 60000 random ENDF-6 files Sometimes deviation from Gaussian shape Rochman, Koning, van der Marck Ann Nuc En 36, 810 (2009) Yields uncertainties on benchmarks

52. 52 Application: SFR void coefficient KALIMER-600 Sodium Fast Reactor (Korea) Total Monte Carlo with MCNP Uncertainties due to Na alone: D. Rochman et al NIM A612, 374 (2010) Uncertainties due to major actinides: see D. Rochman presentation Extension to SFR burn-up underway

53. 53

54. 54 TMC: Other possibilities Random thermal scattering data libraries (?) Random decay data libraries Random fission yield libraries Extension to activation/transmutation codes Optimization to integral benchmarks using e.g. simulated annealing (“search for the best random file”)

55. 55 Conclusions Nuclear data evaluation can be made much more efficient. The secret: Save the essential results of a data evaluation not in a data library but one step before that: -TALYS input parameters + uncertainties -Resonance parameters + uncertainties -Nuclide specific scripts Reproduce everything you want from that The first two applications -Talys Evaluated Nuclear Data Library (TENDL) -Total Monte Carlo