Abstract
Many complex phenomena and the analysis of large and complex system and network can only be studied
adopting advanced computational methods. In addition, in many engineering fields virtual prototypes are used to support
and drive the design of new components, structures and systems. Uncertainty quantification is a key requirement and
challenge for a realistic and reliable numerical modelling and prediction that spans across various disciplines and industry
as well.
The treatment of uncertainty required the availability of efficient algorithms and computational techniques able to
reduce the computational cost required by the non-deterministic analysis and to interface with opensource and commercial
model (e.g. FE/CFD) and libraries. In order to satisfy these requirements and allowing the inclusion of non-deterministic
analyses as a practice standard routing in scientific computing, a general purpose software for uncertainty quantification
and risk assessment, named COSSAN, is under continuous development.
This paper presents an overview of the main capabilities of the recent release of the Matlab open source toolboxes
OPENCOSSAN. The new release includes interfaces with 3rd party libraries allowing to couple OPENCOSSAN with the
state-of-the-art tools in Machine Learning and Meta-modelling. In addition, new toolboxes for reliability and resilient
analysis of system and network are also presented. OPENCOSSAN is released under the Lesser GNU licence. It is
therefore freely available. It is also be package as a Python or Java library for distribution to end users who do not need
MATLAB.
adopting advanced computational methods. In addition, in many engineering fields virtual prototypes are used to support
and drive the design of new components, structures and systems. Uncertainty quantification is a key requirement and
challenge for a realistic and reliable numerical modelling and prediction that spans across various disciplines and industry
as well.
The treatment of uncertainty required the availability of efficient algorithms and computational techniques able to
reduce the computational cost required by the non-deterministic analysis and to interface with opensource and commercial
model (e.g. FE/CFD) and libraries. In order to satisfy these requirements and allowing the inclusion of non-deterministic
analyses as a practice standard routing in scientific computing, a general purpose software for uncertainty quantification
and risk assessment, named COSSAN, is under continuous development.
This paper presents an overview of the main capabilities of the recent release of the Matlab open source toolboxes
OPENCOSSAN. The new release includes interfaces with 3rd party libraries allowing to couple OPENCOSSAN with the
state-of-the-art tools in Machine Learning and Meta-modelling. In addition, new toolboxes for reliability and resilient
analysis of system and network are also presented. OPENCOSSAN is released under the Lesser GNU licence. It is
therefore freely available. It is also be package as a Python or Java library for distribution to end users who do not need
MATLAB.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the joint ICVRAM ISUMA UNCERTAINTIES conference |
| Number of pages | 12 |
| Publication status | Published - 8 Apr 2018 |
| Externally published | Yes |
| Event | Joint ICVRAM ISUMA UNCERTAINTIES conference - Florianolopis, Brazil Duration: 8 Apr 2018 → 11 Apr 2018 http://icvramisuma2018.org/ |
Conference
| Conference | Joint ICVRAM ISUMA UNCERTAINTIES conference |
|---|---|
| Country/Territory | Brazil |
| City | Florianolopis |
| Period | 8/04/18 → 11/04/18 |
| Internet address |
Keywords
- Software
- Uncertainty Quantification
- Reliability
- Resilience
- Networks
- Simulation