Cossan software : a multidisciplinary and collaborative software for uncertainty quantification

Patelli, Edoardo and Broggi, Matto and Tolo, Silvia and Sadeghi, Jonathan; Stefanou, George and Papadrakakis, M. and Papadopoulos, Vissarion, eds. (2017) Cossan software : a multidisciplinary and collaborative software for uncertainty quantification. In: UNCECOMP 2017. National Technical University of Athens, GRC, pp. 212-224. ISBN 9786188284449 (https://doi.org/10.7712/120217.5364.16982)

Preview

Text. Filename: Patelli_etal_UNCECOMP_2017_Cossan_software_a_multidisciplinary_and_collaborative_software.pdf Final Published Version Download (621kB)| Preview

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.

ORCID iDs

Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247

• Share and Export
  

  RefWorksRIS (EndNote Online, Zotero, Ref manager, etc)RDF+XMLEndNoteASCII CitationOpenURL ContextObject in SpanMPEG-21 DIDLRIOXX2 XMLBibTeXAtomEP3 XMLDublin CoreRDF+N-TriplesMODSHTML CitationJSONData Cite XMLRDF+N3Multiline CSVOpenURL ContextObjectReferSimple MetadataMETS
• Item metadata

  Item type:	Book Section
  ID code:	72210
  Dates:	Date Event 17 June 2017 Published
  Subjects:	Social Sciences > Industries. Land use. Labor > Risk Management
  Department:	Faculty of Engineering > Civil and Environmental Engineering
  Depositing user:	Pure Administrator
  Date deposited:	30 Apr 2020 09:47
  Last modified:	11 Nov 2024 15:21
  Related URLs:	Scopus publication
  URI:	https://strathprints.strath.ac.uk/id/eprint/72210