Seaknot: Looking ahead of severe accident research

IF 2.3 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY Annals of Nuclear Energy Pub Date : 2025-03-23 DOI:10.1016/j.anucene.2025.111390
L.E. Herranz , S. Gupta , S. Paci , P. Piluso
{"title":"Seaknot: Looking ahead of severe accident research","authors":"L.E. Herranz ,&nbsp;S. Gupta ,&nbsp;S. Paci ,&nbsp;P. Piluso","doi":"10.1016/j.anucene.2025.111390","DOIUrl":null,"url":null,"abstract":"<div><div>Severe Accidents (SAs) dominate the risk associated to the commercial production of nuclear energy. Despite the major achievements made in their research, still existing gaps, upcoming new technologies as Accident Tolerant Fuels (ATFs) and Small Modular Reactors (SMRs), more stringent safety requirements, optimization of SA management, and other factors, point the need for an efficient use of research resources in the years to come. Three major elements should integrate any SA roadmap to be proposed: preservation of knowledge and know-how; identification of key issues which research would result in the best accident management (AM) feasible; and, no less important, strengthening the workforce who will be responsible for such research. The SEAKNOT project (SEvere Accident research and KNOwledge managemenT for LWRs) was born to address this need in all and every aspect. The present article outlines the major pillars of SEAKNOT and synthesizes the progress made since its onset at the end of 2022. The methodologies adopted to develop a SA PIRT (Phenomena Identification and Ranking Table) and to build a Validation Database Directory (VADD) are described along with the ongoing phenomena listing and ranking. Besides, the first steps towards an experimental infrastructure capable of dealing with present and future needs (SAINET) are included. No less relevant the actions already made and the novelties coming on the side of knowledge and know-how transfer are also discussed.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"218 ","pages":"Article 111390"},"PeriodicalIF":2.3000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Nuclear Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306454925002075","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Severe Accidents (SAs) dominate the risk associated to the commercial production of nuclear energy. Despite the major achievements made in their research, still existing gaps, upcoming new technologies as Accident Tolerant Fuels (ATFs) and Small Modular Reactors (SMRs), more stringent safety requirements, optimization of SA management, and other factors, point the need for an efficient use of research resources in the years to come. Three major elements should integrate any SA roadmap to be proposed: preservation of knowledge and know-how; identification of key issues which research would result in the best accident management (AM) feasible; and, no less important, strengthening the workforce who will be responsible for such research. The SEAKNOT project (SEvere Accident research and KNOwledge managemenT for LWRs) was born to address this need in all and every aspect. The present article outlines the major pillars of SEAKNOT and synthesizes the progress made since its onset at the end of 2022. The methodologies adopted to develop a SA PIRT (Phenomena Identification and Ranking Table) and to build a Validation Database Directory (VADD) are described along with the ongoing phenomena listing and ranking. Besides, the first steps towards an experimental infrastructure capable of dealing with present and future needs (SAINET) are included. No less relevant the actions already made and the novelties coming on the side of knowledge and know-how transfer are also discussed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Seaknot:展望严重事故研究
与核能商业生产相关的风险主要是严重事故(SAs)。尽管他们的研究取得了重大成就,但仍然存在差距,即将出现的新技术,如事故容忍燃料(atf)和小型模块化反应堆(smr),更严格的安全要求,SA管理的优化,以及其他因素,都表明需要在未来几年有效利用研究资源。要提出的任何SA路线图都应包含三个主要要素:知识和技术诀窍的保存;识别关键问题,哪些研究将导致最佳的事故管理(AM)可行;同样重要的是,加强负责此类研究的工作人员队伍。SEAKNOT项目(轻水堆严重事故研究和知识管理)的诞生就是为了从各个方面解决这一需求。本文概述了SEAKNOT的主要支柱,并综合了自2022年底启动以来所取得的进展。本文描述了用于开发SA PIRT(现象识别和排名表)和构建验证数据库目录(VADD)的方法,以及正在进行的现象列表和排名。此外,还包括迈向能够满足当前和未来需求的实验性基础设施(SAINET)的第一步。同样重要的是,已经采取的行动以及知识和技术诀窍转移方面的新颖之处也被讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Annals of Nuclear Energy
Annals of Nuclear Energy 工程技术-核科学技术
CiteScore
4.30
自引率
21.10%
发文量
632
审稿时长
7.3 months
期刊介绍: Annals of Nuclear Energy provides an international medium for the communication of original research, ideas and developments in all areas of the field of nuclear energy science and technology. Its scope embraces nuclear fuel reserves, fuel cycles and cost, materials, processing, system and component technology (fission only), design and optimization, direct conversion of nuclear energy sources, environmental control, reactor physics, heat transfer and fluid dynamics, structural analysis, fuel management, future developments, nuclear fuel and safety, nuclear aerosol, neutron physics, computer technology (both software and hardware), risk assessment, radioactive waste disposal and reactor thermal hydraulics. Papers submitted to Annals need to demonstrate a clear link to nuclear power generation/nuclear engineering. Papers which deal with pure nuclear physics, pure health physics, imaging, or attenuation and shielding properties of concretes and various geological materials are not within the scope of the journal. Also, papers that deal with policy or economics are not within the scope of the journal.
期刊最新文献
Influence of ferric oxide (Fe2O3) content on the mechanical strength and radiation attenuation capacity of concrete Robust and fault-tolerant control of MSBR reactor using a hybrid QFT–PID–LSTM framework with disk margin analysis Effect of molten salt redox states on the chemical behavior of Tellurium: A machine learning molecular dynamics study Transient thermal diffusion analysis and failure prediction in heat-pipe-cooled reactors Transient multiphysics simulations with pin power reconstruction in the Griffin reactor physics code
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1