Development and assessment of a method for evaluating uncertainty of input parameters

Kovtonyuk, A.; Lutsanych, S.; Moretti, Fabio; D'Auria, Francesco Saverio

doi:10.1016/j.nucengdes.2016.08.021

Cited by 16 publications

(11 citation statements)

References 6 publications

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“…The IPREM method, which means Input Parameter Range Evaluation Methodology, was developed at the University of Pisa (UNIPI) [38] [39] [40] for IUQ through comparison of sensitivity calculation results of a system TH code with experimental data. IPREM utilizes the mathematical apparatus of FFTBM (Fast Fourier Transform Based Method).…”

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

“…(4) As illustrated in Figure B.7, there are scenarios in which IPREM will fail, and the user has to manually adjust the limit value for CR. Examples for such failures can be found in [40]. Different limit values can also result in very distinct ranges of variation, so it requires careful engineering characterization.…”

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

“…Therefore, IPREM needs a robust procedure to combine these different results. It was also pointed out in [40] that the choice of the QoIs may significantly affect the resulting parameter ranges, posing challenges and risks in licensing IPREM for regulatory purpose.…”

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

“…Within the PREMIUM project, IPREM was applied by UNIPI [39] [40] to quantify the input uncertainties of the reflood-influential models in RELAP5/Mod3.3. Within the NURESAFE project, IPREM was also applied [40] to quantify uncertainties in the refloodrelated models of the CATHARE2 V2.5 code. The IUQ results were properly verified using data from FEBA and ACHILLES facilities.…”

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

See 3 more Smart Citations

A Comprehensive Survey of Inverse Uncertainty Quantification of Physical Model Parameters in Nuclear System Thermal-Hydraulics Codes

Wu,

Xie,

Alsafadi

et al. 2021

Preprint

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Uncertainty Quantification (UQ) is an essential step in computational model validation because assessment of the model accuracy requires a concrete, quantifiable measure of uncertainty in the model predictions. The concept of UQ in the nuclear community generally means forward UQ (FUQ), in which the information flow is from the inputs to the outputs. Inverse UQ (IUQ), in which the information flow is from the model outputs and experimental data to the inputs, is an equally important component of UQ but has been significantly underrated until recently. FUQ requires knowledge in the input uncertainties which has been specified by expert opinion or user self-evaluation. IUQ is defined as the process to inversely quantify the input uncertainties based on experimental data.This review paper aims to provide a comprehensive and comparative discussion of the major aspects of the IUQ methodologies that have been used on the physical models in system thermal-hydraulics codes. IUQ methods can be categorized by three main groups: frequentist (deterministic), Bayesian (probabilistic), and empirical (design-ofexperiments). We used eight metrics to evaluate an IUQ method, including solidity, complexity, accessibility, independence, flexibility, comprehensiveness, transparency, and tractability. Twelve IUQ methods are reviewed, compared, and evaluated based on these eight metrics. Such comparative evaluation will provide a good guidance for users to select a proper IUQ method based on the IUQ problem under investigation.

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Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

Section: The Iprem Methods Developed By Unipimentioning

confidence: 99%

See 2 more Smart Citations

A Comprehensive Survey of Inverse Uncertainty Quantification of Physical Model Parameters in Nuclear System Thermal-Hydraulics Codes

Wu,

Xie,

Alsafadi

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…•IPREM (Input Parameter Range Evaluation Methodology) based on FFTBM (Fast Fourier Transformation Based Methods) shortly before developed at University of Pisa (UNIPI) (Kovtonyuk et al, 2017) Other existing possibilities were approaches based on extensive using of expert judgement like, "trial-and-error" method by performing calculations of selected experiments related to the investigated phenomenon, definition of "biases", evaluation of information and experience from model development.…”

Section: Phase I: Introduction and Methodology Reviewmentioning

confidence: 99%