TENDL: Complete Nuclear Data Library for Innovative Nuclear Science and Technology
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Otuka, 2014, Towards a more complete and accurate experimental nuclear reaction data library (EXFOR), Nucl. Data Sheets, 120, 272, 10.1016/j.nds.2014.07.065
Mattoon, 2012, Generalized nuclear data: A new structure (with supporting infrastructure) for handling nuclear data, Nucl. Data Sheets, 113, 3145, 10.1016/j.nds.2012.11.008
Koning, 2008, TALYS-1.0, 211
Brown, 2018, ENDF/B-VIII.0: The 8th major release of the nuclear reaction data library with CIELO-project cross sections, new standards and thermal scattering data, Nucl. Data Sheets, 148, 1, 10.1016/j.nds.2018.02.001
Koning, 2008, Towards sustainable nuclear energy: Putting nuclear physics to work, Annals Nucl. En., 35, 2024, 10.1016/j.anucene.2008.06.004
Koning, 2017
Xu, 2013, Databases and tools for nuclear astrophysics applications BRUSsels Nuclear LIBrary (BRUSLIB), Nuclear Astrophysics Compilation of REactions II (NACRE II) and Nuclear NETwork GENerator (NETGEN), Astron. Astrophys. A, 106, 549
Koning, 2012, Modern nuclear data evaluation with the TALYS code system, Nucl. Data Sheets, 113, 2841, 10.1016/j.nds.2012.11.002
Larson, 2008
Sublet, 2011
Cullen, 2017
Mughabghab, 2006
Moxon, 2010, REFIT-2009 A Least-Square Fitting Program for Resonance Analysis of Neutron Transmission, Capture, Fission and Scattering Data
Rochman, 2017, Radiative neutron capture: Hauser Feshbach vs. statistical resonances, Phys. Lett. B, 764, 109, 10.1016/j.physletb.2016.11.018
Rochman, 2013, From average parameters to statistical resolved resonances, Annals Nucl. En., 51, 60, 10.1016/j.anucene.2012.08.015
Rochman, 2008, Pb and Bi neutron data libraries with full covariance evaluation and improved integral tests, Nucl. Inst. Meth. Phys. Res. A, 589, 85, 10.1016/j.nima.2008.02.003
Feshbach, 1947, On the scattering and absorption of particles by atomic nuclei, Phys. Rev., 71, 145, 10.1103/PhysRev.71.145
Forrest, 2007
Kopecky, 1992
Sublet, 2009
Koning, 2003, Local and global nucleon optical models from 1 keV to 200 MeV, Nucl. Phys. A, 713, 231, 10.1016/S0375-9474(02)01321-0
Ribon, 1986, The resonance self-shielding calculation with regularized random ladders, Annals Nucl. En., 13, 209, 10.1016/0306-4549(86)90028-9
Zerovnik, 2011, Influence of resonance parameters' correlations on the resonance integral uncertainty; 55Mn case, Nucl. Inst. Meth. Phys. Res. A, 632, 137, 10.1016/j.nima.2010.12.210
Raynal, 1994
Soukhovitskii, 2004, Global coupled-channel optical potential for nucleon-actinide interaction from 1 keV to 200 MeV, J. Phys. G, 30, 905, 10.1088/0954-3899/30/7/007
Watanabe, 1958, High energy scattering of deuterons by complex nuclei, Nucl. Phys., 8, 484, 10.1016/0029-5582(58)90180-9
Madland, 1988, Recent results in the development of a global medium-energy nucleon-nucleus optical model potential, 103
Avrigeanu, 2014, Further explorations of the alpha-particle optical model potential at low energies for the mass range A=45-209, Phys. Rev. C, 90, 10.1103/PhysRevC.90.044612
Koning, 2008, Global and local level density models, Nucl Phys. A, 810, 13, 10.1016/j.nuclphysa.2008.06.005
Kopecky, 1990, Test of gamma-ray strength functions in nuclear reaction model calculations, Phys. Rev. C, 41, 1941, 10.1103/PhysRevC.41.1941
Capote, 2009, RIPL - reference input parameter library for calculation of nuclear reactions and nuclear data evaluation, Nucl. Data Sheets, 110, 3107, 10.1016/j.nds.2009.10.004
Filipescu, 2014, Photoneutron cross sections for samarium isotopes: Toward a unified understanding of (γ,n) and (n,γ) reactions in the rare earth region, Phys. Rev. C, 90, 10.1103/PhysRevC.90.064616
Hilaire, 2003, Comparisons between various width fluctuation correction factors for compound nucleus reactions, Ann. Phys., 306, 209, 10.1016/S0003-4916(03)00076-9
Koning, 2004, A global pre-equilibrium model from 7 to 200 MeV based on the optical model potential, Nucl. Phys. A, 744, 15, 10.1016/j.nuclphysa.2004.08.013
Qian, 2003, On Monte Carlo methods for Bayesian inference, Ecol. Model., 159, 269, 10.1016/S0304-3800(02)00299-5
Koning, 2015, Bayesian Monte Carlo method for nuclear data evaluation, Eur. Phys. J. A, 51, 184, 10.1140/epja/i2015-15184-x
Helgesson, 2017, Combining Total Monte Carlo and Unified Monte Carlo: Bayesian nuclear data uncertainty quantification from auto-generated experimental covariances, Prog. Nucl. Energy, 96, 76, 10.1016/j.pnucene.2016.11.006
Smith, 2007, A Unified Monte Carlo approach to fast neutron cross section data evaluation, 736
Capote, 2012, A New Formulation of the Unified Monte Carlo Approach (UMC-B) and Cross-Section Evaluation for the Dosimetry Reaction 55Mn(n,γ)56Mn, J. ASTM Int., 9, 10.1520/JAI104115
Bauge, 2011, Evaluation of the Covariance Matrix of 239Pu Neutronic Cross Sections in the Continuum Using the Backward-forward Monte-Carlo Method, J. Kor. Phys. Soc., 59, 1218, 10.3938/jkps.59.1218
Schnabel, 2016, Differential cross sections and the impact of model defects in nuclear data evaluation, EPJ Web Conf., 111, 10.1051/epjconf/201611109001
MacFarlane, 2010, Methods for Processing ENDF/B-VII with NJOY, Nucl. Data Sheets, 111, 2739, 10.1016/j.nds.2010.11.001
Rochman, 2016, Re-evaluation of the thermal neutron capture cross section of 147Nd, Annals Nucl. Energy, 94, 612, 10.1016/j.anucene.2016.03.024
Wahl, 2002
Schmidt, 2016, General Description of Fission Observables: GEF Model Code, Nucl. Data Sheets, 131, 107, 10.1016/j.nds.2015.12.009
Madland, 1982, New calculation of prompt fission neutron spectra and average prompt neutron multiplicities, Nucl. Sci. Eng., 81, 213, 10.13182/NSE82-5
Rochman, 2018, Nuclear data correlation between different isotopes via integral information, EPJ Nucl. Sci. Technol., 4, 7, 10.1051/epjn/2018006
Trkov, 2011
Talou, 2007
Dunford, 1995
Kahler, 2010, Methods for processing ENDF/B-VII with NJOY, Nucl. Data Sheets, 111, 2739, 10.1016/j.nds.2010.11.001
Beck, 2014
Koning, 2012, Modern Nuclear Data Evaluation with the TALYS Code System, Nucl. Data Sheets, 113, 2841, 10.1016/j.nds.2012.11.002
Ge, 2017, CENDL project, the chinese evaluated nuclear data library, EPJ Web Conf., 146, 10.1051/epjconf/201714602002
O. Cabellos, The JEFF-3.3 nuclear data library, 2018, to be published.
Shibata, 2011, JENDL-4.0: A new library for nuclear science and engineering, J. Nucl. Sci. Technol., 48, 1, 10.1080/18811248.2011.9711675
Zsolnay, 2012
Sublet, 2010
Iwamoto, 2016, Photonuclear data file, JAEA-Conf, 2016-004, 53
2000
Watanabe, 2011, Status of JENDL high energy file, J. Kor. Phys. Soc., 59, 1040, 10.3938/jkps.59.1040
2001
Fleming, 2018, HEIR: A High-Energy Intra-Nuclear Cascade Liège-based residual nuclear data library for simulation with FISPACT-II, Nucl. Inst. Meth. Phys. Res. A, 10.1016/j.nima.2018.06.065
Kalbach, 2017, Phenomenological model for light-projectile breakup, Phys. Rev. C, 95, 10.1103/PhysRevC.95.014606
Kalbach, 2005, Preequilibrium reactions with complex particle channels, Phys. Rev. C, 71, 10.1103/PhysRevC.71.034606
Simakov, 2017, Update of the alpha-n yields for reactor fuel materials for the interest of nuclear safeguards, Nucl. Data Sheets, 139, 190, 10.1016/j.nds.2017.01.005
Murata, 2006, Evaluation of the (alpha, xn) reaction data for JENDL/AN-2005, JAEA-Research, 2006-052
Luo, 2011, Cross sections for fast-neutron interaction with erbium isotopes, J. Radioanal. Nucl. Chem., 289, 455, 10.1007/s10967-011-1095-x
Dzysiuk, 2012, Measurement and systematic study of (n, x) cross sections for Dysprosium (Dy), Erbium (Er), and Ytterbium (Yb) isotopes at 14.7 MeV neutron energy, Phys. Rev. C, 86, 10.1103/PhysRevC.86.034609
Amemiya, 1982, Neutron activation cross section of Molybdenum isotopes at 14.8 MeV, J. Nucl. Sci. Technol., 19, 781, 10.1080/18811248.1982.9734218
Cuzzocrea, 1967, Activation cross sections of Mo isotopes for 14.1 MeV neutrons, Nucl. Phys. A, 103, 616, 10.1016/0375-9474(67)90927-X
2015
Fleming, 2015
Bao, 2000, Neutron Cross Sections for Nucleosynthesis Studies, At. Data Nucl. Data Tables, 76, 70, 10.1006/adnd.2000.0838
Dillmann, 2009, KADoNiS v0.3 - The third update of the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars
Rauscher, 2000, Astrophysical reaction rates from statistical model calculations, At. Data Nucl. Data Tables, 75, 1, 10.1006/adnd.2000.0834
Nobre, 2014, Fitting Prompt Fission Neutron Spectra Using Kalman Filter Integrated with Empire Code, Nucl. Data Sheets, 118, 224, 10.1016/j.nds.2014.04.042
Pelloni, 2018, Cross-section adjustment in the fast energy range on the basis of an Asymptotic Progressing nuclear data Incremental Adjustment (APIA) methodology, Annals Nucl. En., 115, 323, 10.1016/j.anucene.2018.01.037
Helgesson, 2017, Combining Total Monte Carlo and Unified Monte Carlo: Bayesian nuclear data uncertainty quantification from auto-generated experimental covariances, Prog. Nucl. Energy, 96, 76, 10.1016/j.pnucene.2016.11.006
Rochman, 2016, A Bayesian Monte Carlo method for fission yield covariance information, Annals Nucl. En., 95, 125, 10.1016/j.anucene.2016.05.005
De Saint Jean, 2015, Evaluation of cross section uncertainties using physical constraints: Focus on integral experiments, Nucl. Data Sheets, 123, 178, 10.1016/j.nds.2014.12.031
Rochman, 2017, Correlation νp-σ-χ in the fast neutron range via integral information, EPJ Nucl. Sci. Technol., 3, 14, 10.1051/epjn/2017009
Rochman, 2011, How to Randomly Evaluate Nuclear Data: A New Data Adjustment Method Applied to 239Pu, Nucl. Sci. Eng., 169, 68, 10.13182/NSE10-66
Rochman, 2012, Evaluation and Adjustment of the Neutron-Induced Reactions of 63,65Cu, Nucl. Sci. Eng., 170, 265, 10.13182/NSE11-37
Leray, 2017, Fission yield covariances for JEFF: A Bayesian Monte Carlo method, EPJ Web Conf., 146, 10.1051/epjconf/201714609023
Bauge, 2015, Full Model Nuclear Data and Covariance Evaluation Process Using TALYS, Total Monte Carlo and Backward-forward Monte Carlo, Nucl. Data Sheets, 123, 201, 10.1016/j.nds.2014.12.035
Helgesson, 2017, Fitting a defect non-linear model with or without prior, distinguishing nuclear reaction products as an example, Rev. Sci. Instrum., 88, 10.1063/1.4993697
Salvatores, 2013
Briggs, 2004
MacFarlane
Sublet, 2017, FISPACT-II: An Advanced Simulation System for Activation, Transmutation and Material Modelling, Nucl. Data Sheets, 139, 77, 10.1016/j.nds.2017.01.002
2018
Leppänen, 2015, The Serpent Monte Carlo code: Status, development and applications in 2013, Annals Nucl. En., 82, 142, 10.1016/j.anucene.2014.08.024
Brun, 2015, TRIPOLI-4, CEA, EDF and AREVA reference Monte Carlo code, Annals Nucl. En., 82, 151, 10.1016/j.anucene.2014.07.053
Gilbert
R.E. MacFarlane, D.W. Muir, R.M. Boicourt, A.C. Kahler, The NJOY Nuclear data processing system – LA-UR-12-27079 (Version 2012-082).
Gilbert, 2015, Energy spectra of primary knock-on atoms under neutron irradiation, J. Nucl. Mater., 467, 121, 10.1016/j.jnucmat.2015.09.023
2015
Oyama, 1988, Measurements and analyses of angular neutron flux spectra on graphite and lithium-oxide slabs irradiated with 14.8 MeV neutrons, J. Nucl. Sci. Technol., 25, 419, 10.1080/18811248.1988.9733610
Ichihara, 2003, Measurement of leakage neutron spectra from a spherical pile of Zirconium irradiated with 14 MeV neutrons and validation of its nuclear data, J. Nucl. Sci. Technol., 40, 417, 10.1080/18811248.2003.9715374
Wong, 1972
Forrest, 2008
Fleming, 2017, TALYS/TENDL verification and validation processes: Outcomes and recommendations, EPJ Web Conf., 146, 10.1051/epjconf/201714602033
Gilbert, 2018
Maekawa, 2000, Decay heat experiment on thirty-two fusion reactor relevant materials irradiated by 14-MeV neutrons, Fusion Eng. Des., 47, 377, 10.1016/S0920-3796(99)00079-4
Maekawa, 1998
Eastwood, 2015, Inventory Uncertainty Quantification using TENDL Covariance Data in Fispact-II, Nucl. Data Sheets, 123, 84, 10.1016/j.nds.2014.12.015
Dzysiuk, 2017, Improving activation cross section data with TALYS, EPJ Web Conf., 146, 10.1051/epjconf/201714602047
Fleming, 2018
Mendoza, 2014, New Standard Evaluated Neutron Cross Section Libraries for the GEANT4 Code and First Verification, IEEE Trans. on Nucl. Sci., 61, 2357, 10.1109/TNS.2014.2335538
Rakhno, 2014, Modelling proton-induced reactions at low energies in the MARS15 code
Haugh, 2017
Capote, 2012, Updating and Extending the IRDF-2002 Dosimetry Library, J. ASTM Int., 9, 1, 10.1520/JAI104119
Rochman, 2016, Nuclear data uncertainty for criticality-safety: Monte Carlo vs. linear perturbation, Annals Nucl. En., 92, 150, 10.1016/j.anucene.2016.01.042
Gilli, 2013, Uncertainty quantification for criticality problems using non-intrusive and adaptive Polynomial Chaos techniques, Annals Nucl. En., 56, 71, 10.1016/j.anucene.2013.01.009
Zhu, 2016, Testing the Sampling-Based NUSS-RF Tool for the Nuclear Data Related Global Sensitivity Analysis with Monte Carlo Neutronics Calculations, Nucl. Sci. Eng., 184, 69, 10.13182/NSE14-142
Cruz, 2014, Uncertainty analysis on reactivity and discharged inventory due to 235,238U, 239,240,241Pu, and fission products: Application to a Pressurized Water Reactor Fuel assembly, Nucl. Technol., 185, 174, 10.13182/NT12-154
da Cruz, 2014, Quantification of Uncertainties due to 235,238U, 239,240,241Pu and Fission Products Nuclear Data Uncertainties for a PWR Fuel Assembly, Nucl. Data Sheets, 118, 531, 10.1016/j.nds.2014.04.126
Rochman, 2014, Nuclear data uncertainty propagation for a typical PWR fuel assembly with bur-nup, Nucl. Eng. Technol., 46, 353, 10.5516/NET.01.2014.712
Rochman, 2017, Nuclear Data Uncertainties for Typical LWR Fuel Assemblies and a Simple Reactor Core, Nucl. Data Sheets, 139, 1, 10.1016/j.nds.2017.01.001
Rochman, 2009, Uncertainties for criticality-safety benchmarks and keff distributions, Annals Nucl. En., 36, 810, 10.1016/j.anucene.2009.01.018
Zhu, 2014, Comparison of Two Approaches for Nuclear Data Uncertainty Propagation in MCNPX for Selected Fast Spectrum Critical Benchmarks, Nucl. Data Sheets, 118, 388, 10.1016/j.nds.2014.04.088
Vasiliev, 2018, On the options for incorporating nuclear data uncertainties in criticality safety assessments for LWR fuel, Annals Nucl. En., 116, 57, 10.1016/j.anucene.2018.01.046
Terranova, 2015, Covariance Matrix Evaluations for Independent Mass Fission Yields, Nucl. Data Sheets, 123, 225, 10.1016/j.nds.2014.12.039
Fiorito, 2016, Generation of fission yield covariances to correct discrepancies in the nuclear data libraries, Annals Nucl. En., 88, 12, 10.1016/j.anucene.2015.10.027
Noguere, 2018, Systematics of Nd cumulative fission yields for neutron-induced fission of 235U, 238U, 238Pu, 239Pu, 240Pu and 241Pu, Eur. Phys. J. Plus, 133, 99, 10.1140/epjp/i2018-11926-y
Leray, 2017, Fission yield covariances for JEFF: A Bayesian Monte Carlo method, EPJ Web Conf., 146, 10.1051/epjconf/201714609023
Sjöstrand, 2017, Propagation of nuclear data uncertainties for fusion power measurements, EPJ Web Conf., 146, 10.1051/epjconf/201714602034
Rochman, 2010, Exact nuclear data uncertainty propagation for fusion neutronics calculations, Fusion Eng. Des., 85, 669, 10.1016/j.fusengdes.2010.03.034
Rochman, 2014, Uncertainty Propagation with Fast Monte Carlo Techniques, Nucl. Data Sheets, 118, 367, 10.1016/j.nds.2014.04.082
da Cruz, 2015, Uncertainty on feedback coefficients and key core parameters for a pressurized water reactor due to nuclear data uncertainties
Rochman, 2011, Uncertainties for the kalimer sodium fast reactor: Void reactivity coefficient, keff, βeff, depletion and radiotoxicity, J. Nucl. Sci. Technol., 48, 1193, 10.1080/18811248.2011.9711807
Alhassan, 2016, Selecting benchmarks for reactor simulations: An application to a lead fast reactor, Annals Nucl. En., 96, 158, 10.1016/j.anucene.2016.05.033
Alhassan, 2015, Uncertainty and correlation analysis of lead nuclear data on reactor parameters for the European Lead Cooled Training Reactor, Annals Nucl. En., 75, 26, 10.1016/j.anucene.2014.07.043
Cabellos, 2014, Propagation of nuclear data uncertainties for PWR core analysis, Nucl. Eng. Technol., 46, 299, 10.5516/NET.01.2014.709
Leray, 2017, Methodology for core analyses with nuclear data uncertainty quantification and application to Swiss PWR operated cycles, Annals Nucl. En., 110, 547, 10.1016/j.anucene.2017.07.006
Rochman, 2018, How inelastic scattering stimulates nonlinear reactor core parameter behaviour, Annals Nucl. En., 112, 236, 10.1016/j.anucene.2017.10.018
da Cruz, 2014, Total Monte Carlo method applied to the assessment of uncertainties in a reactivity-initiated accident
Dokhane, 2018, Validation of PSI best estimate plus uncertainty methodology against SPERT-III reactivity initiated accident experiments, Annals Nucl. En., 118, 178, 10.1016/j.anucene.2018.04.022
Rochman, 2018, Uncertainties for Swiss LWR spent nuclear fuels due to nuclear data, Accept. Eur. J. Phys. N
Rochman, 2018, Consistent criticality and radiation studies of Swiss spent nuclear fuel: The CS2M approach, J. Hazard. Mater., 357, 384, 10.1016/j.jhazmat.2018.05.041
Griffin, 2017, Characterization of the energy-dependent uncertainty and correlation in silicon neutron displacement damage metrics, EPJ Web Conf., 146, 10.1051/epjconf/201714602008