OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties

Patelli, Edoardo; Broggi, Matteo; Angelis, Marco de; Beer, Michael

doi:10.1061/9780784413609.258

Cited by 42 publications

(27 citation statements)

References 13 publications

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“…In this example, the performance of the proposed approaches in robust design optimization of a transmission tower [48,49] has been illustrated. Fig.…”

Section: Example 3: a Transmission Towermentioning

confidence: 99%

A surrogate based multi-fidelity approach for robust design optimization

Chakraborty

Chatterjee

Chowdhury

et al. 2017

Applied Mathematical Modelling

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights • A surrogate based multi-fidelity framework for RDO is proposed. • The first approach is highly efficient and requires very few actual simulations. • Second approach yields highly accurate result from slightly increased simulation.

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“…In this example, the performance of the proposed approaches in robust design optimization of a transmission tower [48,49] has been illustrated. Fig.…”

Section: Example 3: a Transmission Towermentioning

confidence: 99%

A surrogate based multi-fidelity approach for robust design optimization

Chakraborty

Chatterjee

Chowdhury

et al. 2017

Applied Mathematical Modelling

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“…Therefore the variance reduction strategies of Subset Simulation and Importance Sampling were used to obtain P f , and these were compared with the result from Advanced FORM. For both of these algorithms the implementation in the generalized uncertainty quantification software OpenCOSSAN was used (Patelli, 2014 andPatelli, 2016). P f was also calculated with an increased value of the mean value of P, !…”

Section: Validation Of Advanced Formmentioning

confidence: 99%

Structural reliability of pre-stressed concrete containments

Prinja¹,

Ogunbadejo

Sadeghi

et al. 2017

Nuclear Engineering and Design

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This paper presents probabilistic analysis of structural capacity of pre-stressed concrete containments subjected to internal pressure. The conventional design methods for containments are based on allowable stress codes which ensure certain factor of safety between expected load and expected structural strength. Such an approach may give different values of structural reliability in different situations. In recent years, two international round robin exercises have been conducted aimed at predicting the capacity of lined and unlined pre-stressed concrete containments used in nuclear industry. These exercises involved experimental testing and numerical analysis of the models. The first exercise involved ¼ scale steel-lined Pre-stressed Concrete Containment Vessel (PCCV) which was tested at Sandia National Laboratories (SNL) in USA. The second used an unlined containment being tested by the Bhabha Atomic Research Centre (BARC), Tarapur, India. These studies are essentially deterministic studies that have helped validate the analysis methodology and modelling techniques that can be used to predict pre-stressed concrete containment capacity and failure modes. The paper uses these two examples to apply structural reliability method to estimate the probability of failure of the containment. 2 coefficients of variation of the applied pressure and containment radius are the most important parameters. The variability of the probability of failure is decreased at higher pressures, but the coefficients of variation still play an important role.

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“…The algorithms related to the methodology outlined in the former section have been implemented computationally in the general purpose software OpenCossan [15][6], obtaining a complete tool for the reduction and analysis of CNs. The toolbox provides the graphical and numerical implementation of the models as well as the reduction of EBNs to traditional BNs.…”

Section: Computational Toolmentioning

confidence: 99%

Vulnerability of Hydropower Installations to Climate Change: Preliminary Study

Tolo

Patelli

Chen

2017

Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECO

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Abstract. The climate trends observed worldwide over the past few decades appear to corroborate the concerns of the scientific community about the many threats posed by global warming. Future changes of the current climate are expected to occur on different scales all around the globe, hence modifying the environmental background on the basis of which technological installations have been designed and operated. This can potentially threat the safety of the installations as well as their. The development of suitable tools aiming to predict the impact of climate change on technological installations is then essential in the wider context of climate change mitigation. Hydropower installations play often a crucial role not only as a long-term renewable resource of energy but also for flood control and water supply in the case of droughts. All these aspects highlight the increasing importance of such installations as well as their growing vulnerability to natural hazards. It is hence essential to enlarge the current understanding of the interaction mechanisms between such installations and the changing surrounding environment in order to take adequate measures for climate change adaptation and ensure the future safety and productivity of hydropower production. The current study aims to provide a novel model for the evaluation of the impact of climate change on the safety of hydropower stations. The approach adopted allows to include in the model the uncertainty inevitably associated with the input variables and to propagate such uncertainty within the analysis. The model proposed is finally applied to a realistic case-study in order to highlight its potential and limitations.

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OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties

Cited by 42 publications

References 13 publications

A surrogate based multi-fidelity approach for robust design optimization

A surrogate based multi-fidelity approach for robust design optimization

Structural reliability of pre-stressed concrete containments

Vulnerability of Hydropower Installations to Climate Change: Preliminary Study

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