The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

Ikonen, Timo; Tulkki, Ville

doi:10.1016/j.nucengdes.2014.05.015

Cited by 35 publications

(40 citation statements)

References 17 publications

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“…A simple rank transform of the data (for example, the Spearman correlation method) is not sufficient to analyze a fuel performance model comprehensively (Ikonen and Tulkki, 2014). A method that can extract information about the interactions is necessary.…”

Section: Variance Decomposition Analysismentioning

confidence: 99%

“…The calculation of the higher order terms can be done efficiently by Monte Carlo integrals for the first order, second order and total effect indices (Saltelli, 2002;Glen and Isaacs, 2012;Ikonen and Tulkki, 2014). Here one uses a special sampling design to estimate the indices (for the details of the numerical implementation used in this work, we refer the reader to Section 3.4.3 of Ikonen and Tulkki (2014), and the work of Glen and Isaacs (2012)).…”

Section: Variance Decomposition Analysismentioning

confidence: 99%

“…Here one uses a special sampling design to estimate the indices (for the details of the numerical implementation used in this work, we refer the reader to Section 3.4.3 of Ikonen and Tulkki (2014), and the work of Glen and Isaacs (2012)). To evaluate the conditional expectations and variances in Eqs.…”

Section: Variance Decomposition Analysismentioning

confidence: 99%

“…Therefore using Monte Carlo based sensitivity analysis methods is entirely feasible. They have been adopted in many studies to perform global sensitivity analyses (Glaeser, 2008;Boulore et al, 2012;Ikonen and Tulkki, 2014;Pastore et al, 2015). Global sensitivity analysis methods have the advantage of exploring the whole parameter space (hence the term global), and in general can be used to identify properties of very complex models.…”

Section: Introductionmentioning

confidence: 99%

“…For a fuel performance code, the role of interactions in the model can be significant (Ikonen and Tulkki, 2014). This is because of two characteristics of fuel performance codes: large uncertainties in input parameters and complex, non-linear and non-additive structure of the models.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

Ikonen

2016

Nuclear Engineering and Design

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Section: Variance Decomposition Analysismentioning

confidence: 99%

Section: Variance Decomposition Analysismentioning

confidence: 99%

Section: Variance Decomposition Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

Ikonen

2016

Nuclear Engineering and Design

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Assessing the Effect of Some ATF Materials and Uncertainties on Their Properties Under Normal Operation Conditions by Means of the Transuranus Code

Uffelen

Arndt

Soti

2023

Springer Proceedings in Physics

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Actionable insights with less data: guiding early building design decisions with streamlined probabilistic life cycle assessment

Hester

Miller

Gregory

et al. 2018

Int J Life Cycle Assess

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Purpose: Two obstacles that impede wider use of life cycle assessment (LCA) are its time-and data-intensiveness and the credibility surrounding its resultschallenges that grow with the complexity of the product being analyzed.To guide the critical early design stages of a complicated product like a building, it is important to be able to rapidly estimate environmental impacts with limited information, quantify the resulting uncertainty, and identify critical parameters where more detail is needed. Methods:The authors have developed the Building Attribute to Impact Algorithm (BAIA) to demonstrate the use of streamlined (not scope-limiting), probabilistic LCA for guiding the design of a building from early stages of the design process when many aspects of the design are unknown or undecided. Early-design uncertainty is accommodated through under-specificationcharacterizing the design using the available level of detailand capturing the resulting variability in predicted impacts through Monte Carlo simulations. Probabilistic triage with sensitivity analyses identifies which uncertain attributes should be specified further to increase the precision of the results. The speed of the analyses allows for sequentially refining key attributes and re-running the analyses until the predicted impacts are precise enough to inform decision making, such as choosing a preferable design alternative.Results and discussion: Twelve design variants for a hypothetical single-family residential building are analyzed.As information is sequentially added to each variant, the significance of the difference in performance between each variant pair is calculated to determine when enough information has been added to resolve the designs (identify which design is preferable) with high confidence. At the sixth step in the analysis, all variant pairs whose mean impacts differ by at least 4% are resolvable with 90% confidence, even though only 6 attributes are specified and dozens of attributes remain under-specified. Furthermore, the comparative results for each variant pair is validated against a set of conventional LCA results, showing that BAIA identifies the correct preferable design among each resolvable pair at this step. Conclusions:Iterative specification guided by probabilistic triage can help identify promising early design alternatives even when details are only provided for key attributes. The analysis of hypothetical design variants demonstrates that BAIA is both efficient (arrives at statistically defensible conclusions from design variant comparisons based on few pieces of information) and effective (identifies the same preferable design variants as conventional LCAs).

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The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

Cited by 35 publications

References 17 publications

Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

Assessing the Effect of Some ATF Materials and Uncertainties on Their Properties Under Normal Operation Conditions by Means of the Transuranus Code

Actionable insights with less data: guiding early building design decisions with streamlined probabilistic life cycle assessment

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