III. Otras disposiciones. CONSEJO DE SEGURIDAD NUCLEAR. Comunidad Autónoma de Cataluña. Convenio. (BOE-A-2024-212)
Resolución de 26 de diciembre de 2023, del Consejo de Seguridad Nuclear, por la que se publica el Convenio con la Universitat Politècnica de Cataluña, para el desarrollo del proyecto de I+D+i ITHEM ("Técnicas de incertidumbre, termohidráulica avanzada y escalado en metodología de análisis de accidentes").
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Núm. 3
Miércoles 3 de enero de 2024
Sec. III. Pág. 1096
[1] IAEA/SSG-2 rev.0, «Deterministic Safety Analysis for Nuclear Power Plants,» pp.
1–84, 2009.
[2] A. Kovtonyuk, A. Petruzzi, and F. D’Auria, «Post-BEMUSE Reflood Model Input
Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential
Parameters - csni-r2014-14.pdf,» CSNI report, 2014. [Online]. Available: https://
www.oecd-nea.org/nsd/docs/2014/csni-r2014-14.pdf. [Accessed: 13-May-2016].
[3] J. Baccou et al., «Development of good practice guidance for quantification of
thermal-hydraulic code model input uncertainty,» Nucl. Eng. Des., vol. 354, p. 110173,
Dec. 2019.
[4] T. Skorek et al., «Quantification of the uncertainty of the physical models in the
system thermal-hydraulic codes PREMIUM benchmark,» Nucl. Eng. Des., 2019.
[5] J. Freixa, F. Reventós, and E. de Alfonso, «Testing methodologies for quantifying
physical models uncertainties. A comparative exercise using CIRCE and IPREM
( FFTBM ),» Nucl. Eng. Des., vol. 305, pp. 653–665, 2016.
[6] A. de Crécy, «CIRCÉ: A methodology to quantify the uncertainty of the physical
models of a code,» 2012.
[7] A. Kovtonyuk, S. Lutsanych, F. Moretti, and F. D’Auria, «Development and
assessment of a method for evaluating uncertainty of input parameters,» Nucl. Eng. Des.,
vol. 321, pp. 219–229, 2017.
[8] R. Mendizábal, «Bayesian perspective in BEPU licensing analysis,» Nucl. Eng.
Des., vol. 355, p. 110310, Dec. 2019.
[9] D. Wicaksono, O. Zerkak, and A. Pautz, «Bayesian Calibration of ThermalHydraulics Model with Time-Dependent Output,» in NUTHOS-11, 2016, pp. 1–14.
[10] D. Wicaksono, «Bayesian Uncertainty Quantification of Physical Models in
Thermal-Hydraulics System Codes,» PhD Thesis, 2018.
[11] WGAMA, «ATRIUM: CSNI Activity Proposal Sheet ( CAPS ), WGAMA 2021,»
2021.
[12] F. D’Auria, D. Bestion, P. Lien, and H. Nakamura, «THE OECD / NEA / CSNI
SOAR ( State of Art Report ) on Scaling ( THE S- SOAR ),» in NUTHOS-11, 2016, pp. 1–17.
[13] F. Reventos, V. Martínez-Quiroga, and J. Freixa, «Perfecting the use of hybrid
models in scaling analysis,» Nucl. Eng. Des., vol. 354, 2019.
[14] V. M. Martinez Quiroga, «Scaling-up methodology, a systematical procedure for
qualifying NPP nodalizations. Application to the OECD/NEA ROSA-2 and PKL-2
Counterpart test,» Tesis doctoral. Universitat Politècnica de Catalunya, 2014.
[15] V. Martínez-Quiroga, J. Freixa, and F. Reventós, «PVST, a tool to assess the
Power to Volume scaling distortions associated to code simulations,» Nucl. Eng. Des.,
vol. 332, 2018.
[16] V. Martínez-Quiroga, F. Reventós, and J. Freixa, «Applying UPC Scaling-Up
Methodology to the LSTF-PKL Counterpart Test,» Sci. Technol. Nucl. Install., vol. 2014,
pp. 1–18, 2014.
[17] J. Freixa, V. Martínez-Quiroga, and F. Reventós, «Qualification of a full plant
nodalization for the prediction of the core exit temperature through a scaling
methodology,» Nucl. Eng. Des., vol. 308, pp. 115–132, 2016.
[18] J. Freixa, «Modelling guidelines for CCFL representation during IBLOCA
scenarios of PWR reactors» in NURETH-17, 2017.
[19] J. Freixa, V. Martínez-Quiroga, O. Zerkak, and F. Reventós, «Modelling
guidelines for core exit temperature simulations with system codes,» Nucl. Eng. Des.,
vol. 286, pp. 116–129, 2015.
[20] M. Casamor, V. Martínez-Quiroga, F. Reventós, and J. Freixa, «On the Scaling
of Uncertainties in Thermal Hydraulic System Codes,» Ann. Nucl. Energy, 2019.
[21] J. Freixa, V. Martínez-Quiroga, M. Casamor, and F. Reventós, «Validation of a
BEPU methodology through a blind benchmark activity at the PKL test facility» in
NURETH-18, 2019.
cve: BOE-A-2024-212
Verificable en https://www.boe.es
Referencias:
Núm. 3
Miércoles 3 de enero de 2024
Sec. III. Pág. 1096
[1] IAEA/SSG-2 rev.0, «Deterministic Safety Analysis for Nuclear Power Plants,» pp.
1–84, 2009.
[2] A. Kovtonyuk, A. Petruzzi, and F. D’Auria, «Post-BEMUSE Reflood Model Input
Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential
Parameters - csni-r2014-14.pdf,» CSNI report, 2014. [Online]. Available: https://
www.oecd-nea.org/nsd/docs/2014/csni-r2014-14.pdf. [Accessed: 13-May-2016].
[3] J. Baccou et al., «Development of good practice guidance for quantification of
thermal-hydraulic code model input uncertainty,» Nucl. Eng. Des., vol. 354, p. 110173,
Dec. 2019.
[4] T. Skorek et al., «Quantification of the uncertainty of the physical models in the
system thermal-hydraulic codes PREMIUM benchmark,» Nucl. Eng. Des., 2019.
[5] J. Freixa, F. Reventós, and E. de Alfonso, «Testing methodologies for quantifying
physical models uncertainties. A comparative exercise using CIRCE and IPREM
( FFTBM ),» Nucl. Eng. Des., vol. 305, pp. 653–665, 2016.
[6] A. de Crécy, «CIRCÉ: A methodology to quantify the uncertainty of the physical
models of a code,» 2012.
[7] A. Kovtonyuk, S. Lutsanych, F. Moretti, and F. D’Auria, «Development and
assessment of a method for evaluating uncertainty of input parameters,» Nucl. Eng. Des.,
vol. 321, pp. 219–229, 2017.
[8] R. Mendizábal, «Bayesian perspective in BEPU licensing analysis,» Nucl. Eng.
Des., vol. 355, p. 110310, Dec. 2019.
[9] D. Wicaksono, O. Zerkak, and A. Pautz, «Bayesian Calibration of ThermalHydraulics Model with Time-Dependent Output,» in NUTHOS-11, 2016, pp. 1–14.
[10] D. Wicaksono, «Bayesian Uncertainty Quantification of Physical Models in
Thermal-Hydraulics System Codes,» PhD Thesis, 2018.
[11] WGAMA, «ATRIUM: CSNI Activity Proposal Sheet ( CAPS ), WGAMA 2021,»
2021.
[12] F. D’Auria, D. Bestion, P. Lien, and H. Nakamura, «THE OECD / NEA / CSNI
SOAR ( State of Art Report ) on Scaling ( THE S- SOAR ),» in NUTHOS-11, 2016, pp. 1–17.
[13] F. Reventos, V. Martínez-Quiroga, and J. Freixa, «Perfecting the use of hybrid
models in scaling analysis,» Nucl. Eng. Des., vol. 354, 2019.
[14] V. M. Martinez Quiroga, «Scaling-up methodology, a systematical procedure for
qualifying NPP nodalizations. Application to the OECD/NEA ROSA-2 and PKL-2
Counterpart test,» Tesis doctoral. Universitat Politècnica de Catalunya, 2014.
[15] V. Martínez-Quiroga, J. Freixa, and F. Reventós, «PVST, a tool to assess the
Power to Volume scaling distortions associated to code simulations,» Nucl. Eng. Des.,
vol. 332, 2018.
[16] V. Martínez-Quiroga, F. Reventós, and J. Freixa, «Applying UPC Scaling-Up
Methodology to the LSTF-PKL Counterpart Test,» Sci. Technol. Nucl. Install., vol. 2014,
pp. 1–18, 2014.
[17] J. Freixa, V. Martínez-Quiroga, and F. Reventós, «Qualification of a full plant
nodalization for the prediction of the core exit temperature through a scaling
methodology,» Nucl. Eng. Des., vol. 308, pp. 115–132, 2016.
[18] J. Freixa, «Modelling guidelines for CCFL representation during IBLOCA
scenarios of PWR reactors» in NURETH-17, 2017.
[19] J. Freixa, V. Martínez-Quiroga, O. Zerkak, and F. Reventós, «Modelling
guidelines for core exit temperature simulations with system codes,» Nucl. Eng. Des.,
vol. 286, pp. 116–129, 2015.
[20] M. Casamor, V. Martínez-Quiroga, F. Reventós, and J. Freixa, «On the Scaling
of Uncertainties in Thermal Hydraulic System Codes,» Ann. Nucl. Energy, 2019.
[21] J. Freixa, V. Martínez-Quiroga, M. Casamor, and F. Reventós, «Validation of a
BEPU methodology through a blind benchmark activity at the PKL test facility» in
NURETH-18, 2019.
cve: BOE-A-2024-212
Verificable en https://www.boe.es
Referencias:
