CFTR activity is determined store-independently by SPCA2/STIM1/ORAI1 complex in secretory epithelial cells

For several decades, many structures have been monitored during maintenance or during their service lives to analyse long-term behaviour. A large number of sensors, properly distributed in the structure, are necessary, especially if the structure is complex and includes significant spatial variability. When probabilistic modelling is applied, because of intrinsic uncertainties in the model as well as uncertain physical parameters, monitoring measurements can be used to identify the parameters of the structural model. This paper presents a monitoring example of a pile-supported wharf in which tie rods are instrumented and the geotechnical characteristics of the soil embankment are identified. The modelling is performed using a meta-model fitted with a numerical database obtained from direct simulations with a finite element model implemented with Plaxis. A full quadratic response surface model (RSM) is the most efficient approximation to fit the original finite element model. The identified soil parameters enable the model to describe the variability of the measured loading in the tie rods.