A Resilience Modelling Framework for Improved Nuclear Safety (NuRes)
Lead Research Organisation:
University of Liverpool
Department Name: Civil Engineering and Industrial Design
Abstract
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Organisations
Publications
Estrada-Lugo H
(2020)
Resilience Assessment of Safety-Critical Systems with Credal Networks
Morais C
(2022)
Robust data-driven human reliability analysis using credal networks
in Reliability Engineering & System Safety
Morais C
(2022)
Identification of human errors and influencing factors: A machine learning approach
in Safety Science
Morais C
(2020)
Analysis and Estimation of Human Errors From Major Accident Investigation Reports
in ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Related Projects
| Project Reference | Relationship | Related To | Start | End | Award Value |
|---|---|---|---|---|---|
| EP/R020558/1 | 01/01/2019 | 30/11/2019 | £218,436 | ||
| EP/R020558/2 | Transfer | EP/R020558/1 | 01/12/2019 | 31/12/2021 | £159,132 |
| Description | An approach for resilience assessment of nuclear systems under severe threat scenarios using dynamic Bayesian network has been developed. The proposed method integrates all the resilience aspects into a single threat model of the reactor system and quantifies availability as resilience metric for various threat sequences. The quantitative resilience metrics of the reactor system under a threat provides insights on the importance of different factors to decision making process in terms of the resources within the system and for probable improvements to build effective resilience. |
| Exploitation Route | As this novel approach provides an integrated view of the overall reactor system under a threat, it is useful for the practitioners to employ this approach to critical infrastructure systems to assess the resilience. |
| Sectors | Digital/Communication/Information Technologies (including Software) Energy |
| Description | The proposed approach has been employed to a safety-related system of a nuclear reactor to assess the resilience subjecting to various threat scenarios. The resilience metrics for all the possible threat sequences have been quantified which are helpful in logical decision making. A book chapter reviewing the state-of-the-art in resilience engineering has been published and research journal papers are in preparation. |
| First Year Of Impact | 2020 |
| Sector | Digital/Communication/Information Technologies (including Software),Energy |
| Description | Enhanced Methodologies for Advanced Nuclear System Safety (eMEANSS) |
| Amount | £854,922 (GBP) |
| Funding ID | EP/T016329/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2022 |
| End | 11/2025 |
| Description | FIS360 Innovation Consultant |
| Amount | £25,000 (GBP) |
| Funding ID | NNL/GC_551 |
| Organisation | National Physical Laboratory |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 12/2021 |
| End | 03/2022 |
| Description | NDA Bursary scholarship |
| Amount | £65,000 (GBP) |
| Organisation | National Nuclear Laboratory |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2020 |
| End | 09/2024 |
| Title | Toolboox for OpenCossan |
| Description | OpenCOSSAN is a tool for uncertainty quantification and management. It represents the core of COSSAN software under continuous development at the Institute for Risk and Uncertainty,University of Liverpool, UK. All the algorithms and methods have been coded in a Matlab toolbox allowing numerical analysis, reliability analysis, simulation, sensitivity, optimization, robust design. OpenCossan is coded exploiting the object-oriented Matlab programming environment, where it is possible to define specialized solution sequences, which include reliability methods, sensitivity analysis, optimization strategies, surrogate models and parallel computing strategies. The computational framework is organized in packages. A package is a namespace for organizing classes and interfaces in a logical manner, which makes large software project OpenCossan easier to manage. A class describes a set of objects with common characteristics such as data structures and methods. Objects, that are instances of classes can be aggregated forming more complex objects and proving solutions for practical problem in a compact, organized and manageable format. The structure of the software allows for extensive modularity and efficient code re-utilization. Objects (instances of a class) can be aggregated forming more complex objects with methods providing solutions for practical problem in a compact, organized and manageable format. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | Bayesian Belief Networks, more commonly known as Bayesian Networks, are a probabilistic graphical model based on the use of directed acyclic graphs, integrating graph theory with the robustness of Bayesian statistics. The graphical framework of such models consists of nodes, representing the variables of the problem of interest, connected to each other by edges, generally arrows, that depict the dependency link existing between two nodes. The main aim of the Bayesian Network approach is to factorize the probability of a complex event exploiting the knowledge regarding the dependencies existing among its sub-parts. In order to overcome the limitations associated with traditional Bayesian Networks, the integration of such approach with the imprecise probability theory has attracted increasing attention in the scientific community leading to the formulation and study of Credal Networks. Further efforts and research are strongly required in order to enhance the attractivness of Credal Networks outside the academic world and to ensure the reliability and efficiency of their performance in real-world applications. These aims represent the core of the Credal Networks toolbox developed within the OpenCossan framework: well known and novel methodologies are integrated in the software in order to provide the implementation, manipulation and analysis of Credal Networks. |
| URL | http://www.cossan.co.uk/software/open-cossan-engine.php |
| Description | Workshop on Human Reliability and Intelligent and Autonomous systems |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The Centre for Intelligent Infrastructure, University of Strathclyde hosted a two-day workshop "Human Reliability and Intelligent and Autonomous systems" during 26-27, November 2019 as a part of NuRes project (A Resilience Modelling Framework for Improved Nuclear Safety - NuRes). The main objective of this workshop was to foster research and collaborations on methods, applications, related to novel domains for human reliability, intelligent and autonomous systems, the interaction with cyber threats and the consequences on resilience of systems. The workshop comprised of presentations from members of the Committee on Human Factors and Human Reliability of the European Safety and Reliability Association (ESRA) Technical and from researchers from the NuRes project. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://sites.google.com/view/workshop-human-reliability/home |