Trainee Project
Sensitivity analysis of time-varying parameters: application to green roof model
2023/03/06 - 2023/08/25
In many industrial fields, when a highly technical system is under study, simulation codes are used to model, analyze and predict complex physical phenomena. From a given set of input physical parameters, the simulation code computes some quantities of interest, the output variables, that describe the dynamics of the physical system. Input parameters are often affected by aleatory uncertainty due to natural variability or lack of knowledge. While building and using numerical simulation models, sensitivity analysis methods are invaluable tools. They allow to study how the uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model parameters. It may be used to determine the most contributing parameters to an output behavior as the non-influential parameters, or ascertain some interaction effects within the model. The objectives of sensitivity analysis are numerous; one can mention model verification and understanding, model simplifying and factor prioritization. Finally, the sensitivity analysis is an aid in the validation of a computer code, guidance research efforts, or the justification in terms of system design safety.

The first objective of the work is to make a survey of sensitivity analysis approaches existing in the literature [1,2]. A particular interest will be given to approaches that can handle the case of uncertain functional parameters [3], for instance time-varying parameters.

The second objective is to perform the sensitivity analysis of a green roof model.
In her PhD thesis, Axelle Hégo [4] has proposed an original method to take into account the uncertainty of time-varying parameters, as the meteorological parameters, involved in the green roof model. The aim is to apply the method proposed by Axelle Hégo in order to analyse the effect of the meteorological parameters on the volumetric water content of the roof, over different time period presenting some hydrological phenomena of interest.


[1] A. Saltelli, et al. Global Sensitivity Analysis. The Primer. Editions Wiley, 2008.

[2] R. Faivre, et. al. Analyse de sensibilité et exploration de modèles. Application aux sciences de la nature et de l'environnement. Editions Quae, 2016.

[3] E. H. Sandoval, et. al. Sensitivity study of dynamic systems using polynomial chaos. Reliability Engineering and System Safety, Elsevier, 2012, 104, pp.15-26.

[4] A. Hégo, Analyse de sensibilité sur un modèle hydrologique de toiture végétalisée. Université de Lorraine, octobre 2022.
Control Identification Diagnosis