Total Monte Carlo and related applications of the TALYS code system

Arjan Koning

NRG Petten, the Netherlands

Technical Meeting on Neutron Cross-Section Covariances

September 27-30 2010, IAEA, Vienna

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Contents

• Introduction: TALYS code system• Implications and possibilities:

- Large scale nuclear data library production (TENDL)- “Total” Monte Carlo uncertainty propagation- Random search for the best data library

• Conclusions

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TALYS code system

A loop over nuclear physics, data libraries, processing and applications:

• Resonance parameters + uncertainties• An EXFOR database with more uncertainties than errors • The TALYS code • The Reference Input Parameter Library (RIPL)• Software for remaining reaction types (nubar, fns + unc.)• For many nuclides: A set of adjusted model parameters +

uncertainties + “non-physical evaluation actions”• All major world libraries• The ENDF-6 formatting code TEFAL• NJOY, MCNP(X) + other codes• A script that drives everything

The secret: Insist on absolute reproducibility

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ResonanceParameters

.TARES

Experimental data

(EXFOR)

Nucl. model parameters TALYS

TEFAL

Output

Output

ENDFGen. purpose

file

ENDF/EAFActiv. file

NJOY

PROC.CODE

MCNP

FIS-PACT

Nuclear data scheme + covariances

-K-eff

-Neutron flux

-Etc.

-activation

- transmutation

Determ.code

Other(ORIGEN)

+Uncertainties

+Uncertainties

+Covariances

+Covariances +Covariances

+(Co)variances

+Covariances

+Covariances

TASMAN

Monte Carlo: 1000 TALYS runs

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Uncertainties for Cu isotopes

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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• Zeroing in on the truth for the whole nuclide chart at once

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TENDL: Complete ENDF-6 data libraries

MF1: description and average fission quantitiesMF2: resonance dataMF3: cross sectionsMF4: angular distributionsMF5: energy spectraMF6: double-differential spectra, particle yields and residual productsMF8-10: isomeric cross sections and ratiosMF12-15: gamma yields, spectra and angular distributionsMF31: covariances of average fission quantities (TENDL-2010)MF32: covariances of resonance parametersMF33: covariances of cross sectionsMF34: covariances of angular distributionsMF35: covariances of fission neutron spectra (TENDL-2010) and

particle spectra (TENDL-2011)MF40: covariances of isomeric data (TENDL-2011)

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IAEA covariance visualisation system (V. Zerkin)

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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. (Koning and Rochman, Ann Nuc En 35, 2024 (2008)

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ResonanceParameters

.TARES

Experimental data

(EXFOR)

Nucl. model parameters TALYS

TEFAL

Output

Output

ENDFGen. purpose

file

ENDF/EAFActiv. file

NJOY

PROC.CODE

MCNP

FIS-PACT

Nuclear data scheme + covariances

-K-eff

-Neutron flux

-Etc.

-activation

- transmutation

Determ.code

Other(ORIGEN)

+Uncertainties

+Uncertainties

+Covariances

+Covariances +Covariances

+(Co)variances

+Covariances

+Covariances

TASMAN

Monte Carlo: 1000 TALYS runs

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ResonanceParameters

.TARES

Experimental data

(EXFOR)

Nucl. model parameters TALYS

TEFAL

Output

Output

ENDFGen. purpose

file

ENDF/EAFActiv. file

NJOY

PROC.CODE

MCNP

FIS-PACT

Nuclear data scheme: Total Monte Carlo

-K-eff

-Neutron flux

-Etc.

- activation

- transmutation

Determ.code

Othercodes

+Uncertainties

+Uncertainties

+Covariances

+Covariances

TASMAN Monte Carlo: 1000 runs of all codes

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Application: criticality benchmarks

Total of 60000 random ENDF-6 files

Sometimes deviation from Gaussian shape

Rochman, Koning, van der MarckAnn Nuc En 36, 810 (2009)

Yields uncertainties on benchmarks

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Covariance versus Total Monte Carlo

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 (MF36), etc. not obvious- Requires special processing- Requires covariance software for application codes

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Application: SFR void coefficient

• KALIMER-600 Sodium Fast Reactor (Korea)

• Total Monte Carlo with MCNP and FISPACT

• Uncertainties due to transport libraries only, but for all materials

• Sensitivity profiles with MCNP

• K-eff, void coefficient, burn-up and radiotoxicity using TMC

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The total uncertainty is underestimated. Uncertainties for:• Activation cross sections• Fission yield data• Decay dataAre not (yet) taken into account.

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TMC: Other possibilities

• Random thermal scattering data libraries (?)

• Random decay data libraries

• Random fission yield libraries

• Normalization to experimental data or other nuclear data libraries at the basic input level (TENDL-2010)

• Optimization to integral benchmarks using e.g. simulated annealing (“search for the best random file”)

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Optimization of Pu-239

• Select 120 ICSBEP benchmarks

• Create 630 random Pu-239 libraries, all within, or closely around, the uncertainty bands

• Do a total of 120 x 630 =75600 MCNP criticality calculations

• Do another 120 x 4 calculations:

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Optimization of Pu-239

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Optimization of Pu-239

• 6% of libraries have lower chi-2 than JEFF-3.1

• Library #307 has the lowest

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Conclusions

• To improve evaluated libraries, TMC is an easier tool than covariances + perturbation + sensitivity

• However, the world wants covariances, and they get covariances (TENDL)

• With a reproducible automated system, almost anything is possible. After some years of serious software development we can now fork into various branches:- TALYS Evaluated Nuclear Data Library (TENDL)

including complete covariance data (MF31-35)- Total Monte Carlo uncertainty propagation- Nuclear data library optimization- Other applications (not discussed here)

The results of all improvements in uncertainly handling (UMC, model uncertainties, etc.) will be directly visible