Details
| Original language | English |
|---|---|
| Title of host publication | UNCECOMP 2017 |
| Subtitle of host publication | Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering |
| Editors | George Stefanou, M. Papadrakakis, Vissarion Papadopoulos |
| Pages | 212-224 |
| Number of pages | 13 |
| ISBN (electronic) | 9786188284449 |
| Publication status | Published - 2017 |
| Event | 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017 - Rhodes Island, Greece Duration: 15 Jun 2017 → 17 Jun 2017 |
Publication series
| Name | UNCECOMP 2017 - Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering |
|---|---|
| Volume | 2017-January |
Abstract
Computer-Aided modelling and simulation is now widely recognised as the third 'leg' of scientific method, alongside theory and experimentation. Many phenomena can be studied only by using computational processes such as complex simulations or analysis of experimental data. In addition, in many engineering fields computational approaches and virtual prototypes are used to support and drive the design of new components, structures and systems. A general purpose software for uncertainty quantification and risk assessment, named COSSAN, is under continuous development. This is a multi-disciplinary software that satisfies industry requirements regarding numerical efficiency and analysis of detailed models that can be used to solve a wide range of industrial and scientific problems. The main aim of the COSSAN software is to allow the inclusion of non-deterministic analyses as a practice standard routing in scientific computing. This paper presents two recent toolboxes added to the OPENCOSSAN: Credal Networks and Interval Predictive model.
Keywords
- COSSAN-X, OpenCOSSAN, Risk assessment, Uncertainty quantification
ASJC Scopus subject areas
- Computer Science(all)
- Computational Theory and Mathematics
- Computer Science(all)
- Computer Science Applications
- Mathematics(all)
- Theoretical Computer Science
Cite this
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UNCECOMP 2017: Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering. ed. / George Stefanou; M. Papadrakakis; Vissarion Papadopoulos. 2017. p. 212-224 (UNCECOMP 2017 - Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering; Vol. 2017-January).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Cossan software
T2 - 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017
AU - Patelli, Edoardo
AU - Broggi, Matteo
AU - Tolo, Silvia
AU - Sadeghi, Jonathan
N1 - Publisher Copyright: © 2017 The Authors. Published by Eccomas Proceedia. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - Computer-Aided modelling and simulation is now widely recognised as the third 'leg' of scientific method, alongside theory and experimentation. Many phenomena can be studied only by using computational processes such as complex simulations or analysis of experimental data. In addition, in many engineering fields computational approaches and virtual prototypes are used to support and drive the design of new components, structures and systems. A general purpose software for uncertainty quantification and risk assessment, named COSSAN, is under continuous development. This is a multi-disciplinary software that satisfies industry requirements regarding numerical efficiency and analysis of detailed models that can be used to solve a wide range of industrial and scientific problems. The main aim of the COSSAN software is to allow the inclusion of non-deterministic analyses as a practice standard routing in scientific computing. This paper presents two recent toolboxes added to the OPENCOSSAN: Credal Networks and Interval Predictive model.
AB - Computer-Aided modelling and simulation is now widely recognised as the third 'leg' of scientific method, alongside theory and experimentation. Many phenomena can be studied only by using computational processes such as complex simulations or analysis of experimental data. In addition, in many engineering fields computational approaches and virtual prototypes are used to support and drive the design of new components, structures and systems. A general purpose software for uncertainty quantification and risk assessment, named COSSAN, is under continuous development. This is a multi-disciplinary software that satisfies industry requirements regarding numerical efficiency and analysis of detailed models that can be used to solve a wide range of industrial and scientific problems. The main aim of the COSSAN software is to allow the inclusion of non-deterministic analyses as a practice standard routing in scientific computing. This paper presents two recent toolboxes added to the OPENCOSSAN: Credal Networks and Interval Predictive model.
KW - COSSAN-X
KW - OpenCOSSAN
KW - Risk assessment
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85036521479&partnerID=8YFLogxK
U2 - 10.7712/120217.5364.16982
DO - 10.7712/120217.5364.16982
M3 - Conference contribution
AN - SCOPUS:85036521479
T3 - UNCECOMP 2017 - Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering
SP - 212
EP - 224
BT - UNCECOMP 2017
A2 - Stefanou, George
A2 - Papadrakakis, M.
A2 - Papadopoulos, Vissarion
Y2 - 15 June 2017 through 17 June 2017
ER -