| 1. |
- Albiol, T., et al.
(författare)
-
SARNET : Severe accident research network of excellence
- 2010
-
Ingår i: PROG NUCL ENERGY. - : Elsevier BV. ; , s. 2-10
-
Konferensbidrag (refereegranskat)abstract
- Fifty-one organisations network in SARNET (Severe Accident Research NETwork of Excellence) their research capacities in order to resolve the most important pending issues for enhancing, with regard to Severe Accidents (SA). the safety of existing and future Nuclear Power Plants (NPPs). This project. co-funded by the European Commission (EC) under the 6th Framework Programme, has been defined in order to optimise the use of the available means and to constitute sustainable research groups in the European Union. SARNET tackles the fragmentation that may exist between the different national R&D programmes, in defining common research programmes and developing common computer tools and methodologies for safety assessment. SARNET comprises most of the organisations involved in SA research in Europe, plus Canada. To reach these objectives, all the organisations networked in SARNET contributed to a joint Programme of Activities, which consisted of: Implementation of an advanced communication tool for accessing all project information, fostering exchange of information, and managing documents: Harmonization and re-orientation of the research programmes, and definition of new ones; Analysis of the experimental results provided by research programmes in order to elaborate a common understanding of relevant phenomena; Development of the ASTEC code (integral computer code used to predict the NPP behaviour during a postulated SA), which capitalizes in terms of physical models the knowledge produced within SARNET; Development of Scientific Databases in which all the results of research programmes are stored in a common format (DATANET); Development of a common methodology for Probabilistic Safety Assessment of NPPs; Development of short courses and writing a textbook on Severe Accidents for students and researchers; Promotion of personnel mobility amongst various European organisations. This paper presents the major achievements after four and a half years of operation of the network, in terms of knowledge gained, of improvement of the ASTEC reference code, of dissemination of results and of integration of the research programmes conducted by the various partners. After this first period (2004-2008), co-funded by the EC, a further contract SARNET2 with the EC for the next four years started in April 2009 as part of the 7th Framework Programme. During this period, the networking activities will focus mainly on the remaining pending issues as determined during the first period, experimental activities will be directly included in the common work and the network will evolve toward complete self-sustainability. The bases for such an evolution are presented in the last part of the paper.
|
|
| 2. |
- Meyer, Sebastian, et al.
(författare)
-
Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance
- 2017
-
Ingår i: Journal of Statistical Software. - : Foundation for Open Access Statistic. - 1548-7660. ; 77:11
-
Tidskriftsartikel (refereegranskat)abstract
- The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports) in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.
|
|
