Why do we still need nuclear data?

Transcription

1 Why do we still need nuclear data? Arjan Plompen European Commission, Joint Research Centre, Institute for Reference Materials and Measurements Standards for Nuclear Safety, Security and Safeguards (SN3S) unit ec.europa.eu/jrc/en/institutes/irmm

2 Contents Role of nuclear data Needs from sensitivity analyses Needs on the High Priority Request List for nuclear data Other needs (CBRNe) Data adjustment Summary

3 Role of nuclear data Nuclear fission energy Nuclear fusion research Radiation protection Nuclear medicine (Nuclear) security Object and materials analysis Reactions and structure of nuclei Astrophysics Basic science

4 The physical theory of neutron chain reactors Alvin M. Weinberg and Eugene P. Wigner, University of Chicago Press (1958)

5 Nuclear Reactor Physics Weston M. Stacey, Wiley-VCH, 2nd ed. (2007) PART 1 BASIC REACTOR PHYSICS 1 Neutron Nuclear Reactions Neutron-Induced Nuclear Fission Neutron Capture Neutron Elastic Scattering Summary of Cross-Section Data Evaluated Nuclear Data Files Elastic Scattering Kinematics 27 2 Neutron Chain Fission Reactors 33

6 So, our peers told us so, both in the past and still: Nuclear data are important to understand and quantify the processes in a reactor and the fuel cycle as a whole.

7 Role of nuclear data How well can we calculate neutron fields, reaction rates, nuclide inventories, radioactivity, dose rates, decay heat,? What is the penalty for inaccuracy? Safety margins for reactivity, power distribution, reactivity coefficients, burnup/time to refuel, enrichment, shielding, spent fuel storage, Limits what we may learn from expensive integral experiments. Boltzmann: Neutron transport Bateman: Nuclide evolution

8 Role of nuclear data SRIA 2013 Sustainable Nuclear Energy Technology Platform

9 Role of nuclear data SRIA 2013 Sustainable Nuclear Energy Technology Platform Innovation in nuclear energy ESNII European Sustainable Nuclear Infrastructure Initiative ASTRID ALFRED MYRRHA ALLEGRO

10 Role of nuclear data SRIA 2013 Sustainable Nuclear Energy Technology Platform

11 Role of nuclear data SRIA 2013 Sustainable Nuclear Energy Technology Platform

12 Role of nuclear data SRIA 2013 Sustainable Nuclear Energy Technology Platform

13 Role of nuclear data

14 Conditioned by the future of nuclear energy Safety is first of all engineering & operational. Nuclear data: Reliability of assessments. Margins for the engineers. Cost of new developments: design and interpretation of testing, mock-up experiments. Decommissioning. Material composition and history most important. Not much interest in data. Nuclear waste For some countries the only remaining point of concern.

15 So, nuclear data have a role to play in preparing innovation in nuclear energy. Nuclear data have this role supporting other disciplines that are more hands on and thus easier to defend. In view of the history of nuclear data detailed motivation in the current context is essential. This is not any different for the other disciplines! The speed of innovation is slow. Many promising developments have yet to prove their value.

16 Sensitivity analysis Quantitative underpinning of requests System modeling A simple principle Conceptual systems Group cross sections p f Future i. Better capabilities ii. More modeling iii. Actual designs (design dependence) iv. Better feedback from experiments

17 Sensitivity analysis Back propagation r i (x): relative uncertainty of x Leave a domain of acceptable uncertainties Allows a range of solutions that is hard to visualize or delineate Cost function minimization is used to find the best route to the final goal An r a (p) more accurate than needed will relax requirements on other parameters r i (x): relative uncertainty of x

18 Sensitivity analyses Subgroup-26 Final report and several additional references (Salvatores et al., Aliberti et al.) Fast reactors ABTR, EFR, SFR (Na) LFR, ADMAB (Pb) GFR (gas) Thermal reactors PWR VHTR N. Garcia Herranz et al., Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations, Ann.Nucl.En. 35 (2008) 714 N. Garcia Herranz et al., Nuclear data requirements for the ADS conceptual design EFIT: uncertainty and sensitivity study, Ann. Nucl. En. 37 (2010) 1570

19 Subgroup-26 tables per system Very tight requirements; accurate measurements are required

20 Overview of SG-26 conclusions; partly on HPRL

21 Are there new insights since SG-26? UPM, CIEMAT, UNED (2010) EFIT ADS Pb-ADS industrial transmuter, Fuel cycle = nuclide inventories CS but no DD uncertainties 150 GWd/t in 2y (= 1 cycle). Multiple cycles. Max 500 GWd/t. Cooling up to y. Target unc: 5% inventory 10% response functions Conclusions Inventories: may exceed 10% at 150 and 500 GWd/t Decay heat: within 10% always Neutron source: Cm and Cf SF dominated 500 GWd/t:10-30% u Dose rates: within 10% always Needs: U-Cf, except 238 U Fission for all fissiles Capture for nonfissiles Target uncertainty table 2.5-7%

22 Are there new insights since SG-26? System dependence can be significant despite superficial similarity: sensitivity analysis for actual choices needed!

23 Actinides on the HPRL 23 of the 36 requests concern actinides 3 of 23 requests are exclusively thermal-resolved resonance region. Rest cover the unresolved region and the lower fast region (< 6 MeV). Few cases up to 10 or 20 MeV. For completeness and consistency, modeling is essential. All cross sections (total and partial, all energies). All physics aspects (spectra, ddx). In most cases the result should be very accurate. Detailed reproduction of high quality measurements. Account for important physics aspects that are known. Implement these without approximation. Identify what is not done yet. Account for remaining model defects October 2014

24 Overview High Priority Request List High priority requests (1) Fission 238 Pu(n,f) sig, nubar 239 Pu, 235 U prompt gammas, 7.5%, 0-10MeV 240 Pu(n,f) sig, nubar 241 Pu(n,f) 242 Pu(n,f) 241 Am(n,f) 242m Am(n,f) 242 Cm(n,f) 244 Cm(n,f) 245 Cm(n,f) Capture 12 C(n,g) 5%, epith. Hf(n,g) 4% 0.5-5keV 235 U(n,g) 100eV-1MeV 3% 238 U(n,g) 239 Pu(n,g) 241 Pu(n,g) 241 Am(n,g+T)

25 Overview High Priority Request List High priority requests (2) Scattering 2 H(n,n) 5% 0.1-1MeV DA 23 Na(n,n ) 56 Fe(n,n ) 28 Si(n,n ) 206 Pb(n,n;) 207 Pb(n,n ) 209 Bi(n,n ) 238 U(n,n ) (2%) 243 Am(n,n ) Reactions 10 B(n,a) 12 C(n,abs) 6-20MeV 7%

26 Overview High Priority Request List General requests Fission Au(n,T) 5-200keV 233 U(n,g) 9% MeV 233 U(n,f) sig,nubar th-10kev, 0.5% 239 Pu(n,f)/(n,g) eta/alpha 1% 242 Pu(n,g+T) 8% 0.5eV-2keV 243 Am(n,f) n-spectrum th- 10MeV, 10% 244 Cm(n,f) n-spectrum th-10mev, 10% Fusion 28 Si(n,np) 20% 52 Cr(n,xd)/(n,xt) th-65mev 56 Fe(n,xn) 7-20MeV 30%

27 Data adjustment Application libraries adjusted to representative benchmarks May be the only way! Is it understood? Emphasis on k-eff. Few benchmark results determine data changes. Feedback about underlying data? Consistent approach under development. G. Palmiotti and M. Salvatores, Science and Technology of Nuclear Installations Vol. 2012, article , doi: /2012/529623

28 Data adjustment G. Palmiotti and M. Salvatores, Science and Technology of Nuclear Installations Vol. 2012, article , doi: /2012/ Reaction rates/ spectral indicators

29 Data adjustment G. Palmiotti and M. Salvatores, Science and Technology of Nuclear Installations Vol. 2012, article , doi: /2012/ Nuclide densities

30 K-eff is a delicate balance B. Morillon, slide courtesy P. Romain (CEA), INDC(NDS)-0597, A. Plompen, T. Kawano, R. Capote Eds. (2011).

31 K-eff is a delicate balance Partial cross section differences between evaluations have k-eff impacts well beyond the desired uncertainty. Fortuitous cancellations must be expected for both physics model choices and in data adjusment! How cancellations affect predictability out of the domain of benchmarking is even less clear than within the accessible domain. There is no substitute for understanding, and we must continue to improve our understanding despite the ability for/with the aid of massive computation and comparisons.

32 Data adjustment G. Palmiotti and M. Salvatores, Science and Technology of Nuclear Installations Vol. 2012, article , doi: /2012/ Substantial improvements possible C/E Uncertainty of C/E Few systems, many underlying data. Ensure adjusted data remain close to microscopic data. i. This is the job of the consistent approach. ii. Progress is being made but we are not there yet. Residual discrepancies are remarkable! i. Many more parameters than data! ii. Discrepancies should be analysed to understand the physics. iii. More detailed interpretation than k-eff alone seems needed. iv. More integral experiments are expensive, but more quantities from past experiments are available. If it disagrees with experiment, it s wrong. In that simple statement is the key to science, R.P. Feynman, Cornell lecture (1964)

33 CBRNe Chemical, biological, radionuclide, nuclear and explosive defence Considerable political interest Emergency preparedness Forensics Radioactivity Fission products (nuclear data aspect) Induced activity (nuclear data aspect) Dirty bombs Excellent example how good modeling may predict a cross section before the measurement TALYS - BRC, ENDF/B-VII - LANL C. Sage et al. Phys. Rev. C 81 (2010) T. Gorbinet et al. Nuclear Data Week, November 2013, OECD-NEA, Paris

34 So we have motivations for studying nuclear data I will rely on others for needs in fields further from me (you may also check the IAEA and IAEA-NDS websites). Are we ready to tackle them and how? Well, that s just what this workshop is for. So, I will just lean back and observe. After a few more slides.

35 Cross section (mb) Role of nuclear data measurements JEFF-3.1 JENDL-3.3 EAF-2007 ENDF-B/VII 1959 Lindner 1975 Qaim 2006 Avrigeanu 2003 Filatenkov 1993 Grallert 1992 Kasugai W(n,a) 181 Hf Neutron energy (MeV) Nuclear modeling lacks accuracy for detailed predictions of cross sections Resonance parameters are effectively stochastic variables: level energies, partial widths Data are needed for developing models determining model parameters benchmark model parameter databases and overall model performance checks

36 Cross section (mb) Role of nuclear data measurements JEFF-3.1 JENDL-3.3 EAF-2007 ENDF-B/VII 1959 Lindner 1975 Qaim 2006 Avrigeanu 2003 Filatenkov 1993 Grallert 1992 Kasugai W(n,a) 181 Hf Neutron energy (MeV) Nuclear modeling lacks accuracy for detailed predictions of cross sections, however: Modeling is essential for extracting physical parameters from a measurement, interpolating and extrapolating experimental results, making an educated guess about the unmeasurable, providing complete physically consistent databases.

37 Nuclear data challenges HPRL, SG26, NUDATRA Quantatively: Very tight target uncertainties will remain in the picture Fission cross sections (2% for MA, nu-bar, neutron-spectrum) Fissile nuclides capture cross sections (5% or better) Scattering cross sections (2-5%) and angular distributions ( 238 U, 56 Fe, 23 Na) Several issues not tackled for a long time are being picked up Prompt fission gammas Neutron spectra and angular distributions Capture of the main fissile nuclides (In)elastic scattering of U-238 Technical developments are required for tackling these challenges Emphasis on high quality, accurate experiments Experiments to improve nuclear models New detectors and data-acquistion New analysis methods New neutron sources Target preparation and characterisation High level theoretical and evaluation support for generating and validating nuclear data, covariances and their propagation to applications.

38 Joint new efforts, measurement and modeling IPHC and CEA/BRC ESNT Saclay March 2014, Kerveno-Dupuis Slides and calculations M. Dupuis (BRC) QRPA for pre-equilibrium and direct reactions 238 U(n,n g) data IPHC (prelim) and LANL+LLNL

39 Cross section (barns) Joint efforts in modeling Dispersive and Lane consistent coupledchannels OMPs, microscopic OMPs. Investigations in coupling effects. Improved modeling for elastic and inelastic scattering on actinides. Slides courtesy P. Romain (CEA), R. Capote (IAEA), INDC(NDS)-0597, A. Plompen, T. Kawano, R. Capote Eds. (2011) U - ANL EXFOR FLAP 2.2 Soukhovitskii, JPG 2004 (RIPL 2601) DCC Capote&Souk, Unpublished (RIPL 2409) Young et al, 1998, ENDF-B/VII.0 (RIPL 2008) DCC Capote, Soukhovitskii, Chiba, Quesada (curr work) DCC Romain-Duarte-Morillon Bauge et al, BRC semimicroscopic U+n Neutron energy (MeV)

40 Summary Role of data Large scale modeling Nuclear systems design, development and performance estimates. Emphasis on safety analyses Design and interpretation of experiments for cost effective development. Recognised SNETP/SRIA & SRA Recognised EUROSAFE Trends in Europe Nuclear safety Nuclear waste Emergency preparedness Decommissioning Sources of data needs HPRL Sensitivity analyses File projects Literature Challenging needs require High quality experiments High qualtity calculations Technical developments!

41 Two-fold thank you to the organizers: for letting me off the hook first, and for keeping the topic light. Who in pursuit of sciences hunts for immediate practical utility can be rather certain that he will hunt in vain. - Hermann von Helmholtz Über das Verhältnis der Naturwissenschaften zur Gesammtheit der Wissenschaft, Inauguration speech for the office of prorector of the University of Heidelberg (1862). Wer bei der Verfolgung der Wissenschaften nach unmittelbaren parktischem Nutz jagt, kann ziemlich sicher sein, dass er vergebens jagen wird.