Sensitivity Analysis: From Theory to Practice

Saltelli, Andrea; Ratto, Marco; Andres, Terry; Campolongo, Francesca; Cariboni, Jessica; Gatelli, Debora; Saisana, Michaela; Tarantola, Stefano

doi:10.1002/9780470725184.ch6

Cited by 20 publications

(19 citation statements)

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“…Uncertainty analysis focuses on quantifying uncertainty in model output [28] and is a major milestone to analyse complex models [21]. Uncertainty analysis has been widely applied to study the energy performances of individual buildings [29][30][31], highlighting the importance of including both physical and occupants' behaviour related parameters [32].…”

Section: Uncertainty Analysismentioning

confidence: 99%

“…Alternatively, other sensitivity methods may be applied instead of Sobol' method, for instance the Fourier Amplitude Sensitivity Testing -FAST [28]. However, the FAST method is not suitable for discrete distributions and it is not able to consider the interaction effects [15].…”

Section: Design Of the Reference Energy Modelmentioning

confidence: 99%

“…The Elementary Effect (EE) method by Morris [36] is proposed as the screening method as it is simple but effective in identifying the important parameters among the many that can be contained in a model [28,[48][49][50]. The computation cost for the method is r · (p+1) simulations, where p is the number of factors and r is the number of repetitions for the design.…”

Section: Screening Of Input Parametersmentioning

confidence: 99%

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Global sensitivity analysis as a support for the generation of simplified building stock energy models

Mastrucci

Pérez‐López

Benetto

et al. 2017

Energy and Buildings

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International audienceBuildings are responsible for 40% of total final energy consumptions in Europe. Numerous bottom-up models were recently developed to support local authorities in assessing the energy consumption of large building stocks and reduction potentials. However, current models rarely consider uncertainty associated to building usage and characteristics within the stock, resulting in potentially biased results. This study presents a generic model simplification approach using uncertainty propagation and stochastic sensitivity analysis to derive fast simplified (surrogate) models to estimate the current building stock energy use for improved urban planning. The methodology includes an engineering-based energy model as input to global sensitivity analysis (GSA) using the elementary effects (EE) screening and Sobol’ method for key parameters identification and regression analysis to derive simplified models for entire building stocks. The application to the housing stock of Esch-sur-Alzette (Luxembourg) showed that the parameters explaining most of the variability in final energy use for heating and domestic hot water are floor area, set-point temperature, external walls U-values, windows and heating system type. Results of the simplified models were validated against measured data and confirmed the validity of the approach for a simple yet robust assessment of the building stock energy use considering uncertainty and variability

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Section: Uncertainty Analysismentioning

confidence: 99%

Section: Design Of the Reference Energy Modelmentioning

confidence: 99%

Section: Screening Of Input Parametersmentioning

confidence: 99%

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Global sensitivity analysis as a support for the generation of simplified building stock energy models

Mastrucci

Pérez‐López

Benetto

et al. 2017

Energy and Buildings

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“…When a simulation model is utilised, uncertainties in the input parameters are propagated through the model and are echoed in the outputs. Sensitivity analysis (SA) is a statistical method used to quantify how the different inputs contribute to the variability of the outputs [2,20]. A related technique is the uncertainty analysis (UA), which studies the variability of the output results given the uncertainty of the input parameters and is often run in tandem with SA [2,20,21].…”

Section: Sensitivity Analysis To Assess Building Energy Performancementioning

confidence: 99%

Sensitivity analysis of cooling demand applied to a large office building

Zeferina

Wood

Edwards

et al. 2021

Energy and Buildings

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“…Sensitivity analysis ranks input parameters from the most to the least significant ones with respect to the impact their variability has on the total variance of the output of interest. In this work, sensitivity analysis is carried out according to a so-called analyis of variance (ANOVA) principle [38].…”

Section: Sensitivity Analysismentioning

confidence: 99%

Stochastic analysis of the electromagnetic induction effect on a neuron’s action potential dynamics

2021

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This paper examines the effect of electromagnetic induction on the electrophysiology of a single cortex neuron through two different modes associated with the nature of the external neuronal stimulus. By using the recently extended induction-based variant of the well-known and biologically plausible Hodgkin-Huxley neuron model, bifurcation analysis is performed. Electromagnetic induction caused by magnetic flux is captured using a polynomial approximation of a memristor embedded into the neuron model. In order to determine true influence of the variability of ion channels conductivity, the stochastic sensitivity analysis is performed post hoc. Additionally, numerical simulations are enriched with uncertainty quantification, observing values of ion channels conductivity as random variables. The aim of the study is to computationally determine the sensitivity of the action potential dynamics with respect to the changes in conductivity of each ion channel so that the future experimental procedures, most often medical treatments, may be adapted to different individuals in various environmental conditions.

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Sensitivity Analysis: From Theory to Practice

Cited by 20 publications

References 0 publications

Global sensitivity analysis as a support for the generation of simplified building stock energy models

Global sensitivity analysis as a support for the generation of simplified building stock energy models

Sensitivity analysis of cooling demand applied to a large office building

Stochastic analysis of the electromagnetic induction effect on a neuron’s action potential dynamics

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