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New Approach to Reactor Safety ImprovementS

Deliverables

Use of E-BEPU for evaluation of Design Extension Conditions

This deliverable will present the applicability of E-BEPU methodology for DEC analysis and possible benefits it might bring for future NPPs' design (results from sub-task 3.4.3).

Improved methodologies for extreme earthquake hazard assessment

This deliverable will present the implementation of the conditional spectra approach (so-called risk-targeted hazard), as proposed in sub-task 1.2.4.

Review of state-of-the art for hazard and multi-hazard characterisation

This deliverable will present the extensive review of existing multi-hazard approaches and procedures for natural hazard assessment with respect to nuclear hazard and safety, as proposed in task1.1.

Methods to incorporate human factors within a multi-hazard approach

This deliverable will present the method developed to enable integration of human aspects into fragility functions and to investigate their impact on them (cf. task 2.4).

Definition of hazard-induced damage states and development of state-specific APETs for demonstration purposes

This deliverable will provide a map of the key decisions identified in task 5.2, to be made during the implementation of EOP/EDMG/SAMG in response to the considered hazard damage state into the logic of corresponding state-specific APET, developed based on the experience and knowledge from the Level-2 PSA studies (cf. task 5.3).

Methodology to account for soil-structure interactions in the fragility assessment

This deliverable will first present a new simplified modelling technique for seismic SSI with a reduced computation time, hence useful within the framework of PSA process. Second, the proposed model will be compared to existing tools (e.g. SASSI) on well-known NPP case studies, e.g. derived from international benchmarks (see sub-task 2.2.2 for details).

Description of a meta-modelling strategy for probabilistic analyses

This deliverable will present some model reduction strategies applicable for assessing the impact of external hazards (e.g. earthquakes, flooding) on NPPs from a probabilistic perspective (outputs from sub-task 4.2.1).

Development of single and secondary effect hazard assessment methodologies including uncertainty quantification and comparison

This deliverable will provide methods to analyse extreme hazards using multi-varied statistics and to account for secondary hazards associated with each NPP component separately using physical approaches. On the other hand, it will present a stochastic approach to scenario development, allowing characterization of the hazard curve to integrate all possible uncertainty, temporal and spatial combinations for Design Basis Events (see task 1.3 for details).

Improved methodologies for tsunami hazard assessment

This deliverable will present the use and implications of fast GPU computations for PHA on one hand, and on the other hand, the general probabilistic hazard assessment approach to be developed for earthquake-triggered tsunamis (see sub-task 1.2.1 for details).

Methodology to derive vector-based fragility functions I: theoretical aspects

This deliverable will present the general methodology proposed in task 2.3, to design and check elaborate fragility models with respect to multiple intensity measures (i.e. vector-valued), thus harmonizing the response of the NPP SSC to multi-hazard solicitations.

Project presentation brochure

The project brochure will present the main information on the NARSIS project: aims and main expected outcomes, consortium, ...

Improvements of flexible approaches and procedures relying on expert-based information

This deliverable will present the proposed improvement of the current practices in terms of flexible approaches / procedures and uncertainty propagation in relation with expert-based information and knowledge modelling, using recent advanced procedures and tools (cf. task 3.3 for details).

Flooding impact on industrial facilities via advanced numerical modelling

This deliverable will present the results of SPH simulations of a realistic coastal NPP platform for selected flooding event scenarios (tsunami, storm). These results will be analyzed with respect to the requirements of nuclear engineering (see details in sub-task 1.2.3).

Risk integration methods for high risk industries

This deliverable will present a review and comparison of risk integration methods from high risk industries (e.g. aviation, chemical and nuclear industries), with particular emphasis on methods able to incorporate low probability events, multi-hazards, and integration of human, social/organizational and technical aspects (cf. task 3.1). It will also review the deterministic & probabilistic methods for identification of latent weaknesses in complex industrial facilities. Hence, this deliverable merges the contents of former deliverables D3.1 (due on M12) and D3.6 (initially due on M18, but now suppressed).

Improved methodologies for extreme weather and flooding hazard assessment

This deliverable will first report on proposed methods and related uncertainties, to address combination of phenomena in the framework of flooding hazard curves assessment. The probabilistic assessment of failures for some geotechnical safety structures by external hydraulic effects will also be addressed in this deliverable (see details in sub-task 1.2.2).

Communication and Dissemination Plan report

Communication and Dissemination Plan report of the project.

Project Newsletter (e-mailing) - M12

Project Newsletter (e-mailing) - M12

Project Newsletter (e-mailing) - M18

Project Newsletter (e-mailing) - M18

Project Newsletter (e-mailing) - M6

The NARSIS Newsletter will be produced every six months, starting on Month 6.

Project website (activation)

This deliverable is directly linked to task 6.1. The website will serve for public dissemination of project information and deliverables, as well as for the team working area and exchanges.

Publications

Vector intensity measures for a more accurate reliability assessment of NPP sub-systems

Author(s): Gehl , Pierre; Rohmer , Jérémy
Published in: Proc. TINCE 2018, Issue 1, 2018

The Goal of the New Approach to Reactor Safety Improvements (NARSIS) Project

Author(s): Štrubelj, L., Foerster, E., Rastiello, G., Daniell, J., Bazargan-Sabet, B., Gehl, P., Pierre Gehl, Vardon, P. J., Duvvuru Mohan, V. K.
Published in: Proc. 12th International Conference of the Croatian Nuclear Society, Issue 1, 2018

Non incremental LATIN-PGD solver for non-linear vibratoric dynamics problems

Author(s): Rodriguez, S., Néron, D., Charbonnel, P.-E., Ladevèze, P., Nahas, G.
Published in: Proc. CSMA 2019, Issue 1, 2019

Identifying uncertainty contributions to the seismic fragility assessment of a nuclear reactor steam line

Author(s): Gehl, Pierre; Macilhac-Fradin, Marine; Rohmer, Jeremy; Guigueno, Yves; Rahni, Nadia; Clément, Julien
Published in: Proc. COMPDYN 2019, Issue 1, 2019, Page(s) 47-68

Improving the performance of Success Likelihood Index Model (SLIM) using Bayesian network

Author(s): Abrishami, S., Khakzad, N., van Gelder, P.
Published in: Proc. ESREL2019, Issue 1, 2019, Page(s) pp 310-315

Conceptual Design of a Decision Support Tool for Severe Accident Management in Nuclear Power Plants

Author(s): Bohanec, M., Vrbanić, I., Bašić, I., Debelak, K., Štrubelj, L.
Published in: Proc. IS 2019, Issue Volume A - Slovenian Conference on Artificial Intelligence, 2019, Page(s) Pages 5-8

Seismic performance of fuel assemblies based on intensity-compatible sets of recorded ground motion time histories

Author(s): Pellissetti, M., Kessler, H., Schmidl, J., Nykyforchyn, A., Staeuble-Akcay, S.
Published in: Proc. SMiRT 25, 2019, Page(s) IV_861

Uncertainty Tracking and Geotechnical Reliability Updating Using Bayesian Networks

Author(s): Duvvuru Mohan, V.K.; Vardon, P.J.; Hicks, M.A.; van Gelder, P.H.A.J.M.; Ching, Jianye; Li, Dian-Qing; Zhang, Jie
Published in: Proceedings of the 7th International Symposium on Geotechnical Safety and Risk (ISGSR 2019), 2019, Page(s) 631-636

Constraining Input Uncertainty Sources of PSA by Sensitivity Analysis Using FFTBM-SM

Author(s): Andrej Prošek, Andrija Volkanovski
Published in: Proc. NENE2019, Issue 1, 2019, Page(s) pp. 201.1-201.8

Progression of Station Blackout Event in PWR Plant

Author(s): Andrija Volkanovski, Andrej Prošek
Published in: Proc. NENE2019, 2019, Page(s) pp. 1013.1-1013.7

A Bayesian framework for estimating fragility curves based on seismic damage data and numerical simulations by adaptive neural networks

Author(s): Zhiyi Wang, Irmela Zentner, Enrico Zio
Published in: Nuclear Engineering and Design, Issue 338, 2018, Page(s) 232-246, ISSN 0029-5493
DOI: 10.1016/j.nucengdes.2018.08.016

Global Megathrust Earthquake Hazard—Maximum Magnitude Assessment Using Multi-Variate Machine Learning

Author(s): Andreas M. Schäfer, Friedemann Wenzel
Published in: Frontiers in Earth Science, Issue 7, 2019, Page(s) Article 136, ISSN 2296-6463
DOI: 10.3389/feart.2019.00136

An integration of human factors into quantitative risk analysis using Bayesian Belief Networks towards developing a ‘QRA+’

Author(s): W.M.P. Steijn, J.N. Van Kampen, D. Van der Beek, J. Groeneweg, P.H.A.J.M. Van Gelder
Published in: Safety Science, Issue 122, 2020, Page(s) 104514, ISSN 0925-7535
DOI: 10.1016/j.ssci.2019.104514

Uncertainties in conditional probability tables of discrete Bayesian Belief Networks: A comprehensive review

Author(s): Jeremy Rohmer
Published in: Engineering Applications of Artificial Intelligence, Issue 88, 2020, Page(s) 103384, ISSN 0952-1976
DOI: 10.1016/j.engappai.2019.103384

Sensitivity analysis of Bayesian networks to parameters of the conditional probability model using a Beta regression approach

Author(s): Jeremy Rohmer, Pierre Gehl
Published in: Expert Systems with Applications, Issue 145, 2020, Page(s) 113130, ISSN 0957-4174
DOI: 10.1016/j.eswa.2019.113130