Another approach is to measure the break-through curve of the concentration at the outlet as a function of time during the experiment. In both cases, the concentration results are fitted to the predictions of 1D or 2D mass diffusion numerical codes to calculate the diffusivity. In the present work, we benefit from the experimental setup, which allows for the in-situ measurement of concentration evolution across the domain of interest in a non-destructive manner over time. This represents a improvement over studies such as , where only the final concentrations could be determined. This technique allows for the collection of multiple concentration profiles from a single experiment, providing a wealth of temporal data that significantly enhances the modelling efforts. Since the 3D physical solver would require a prohibitive amount of computational time, the inverse modelling of the experimental data needs a procedure to accelerate the computations. Such acceleration is provided by the surrogate ANN model in this paper as described in the previous sections. It is noted that both, the complexity of the numerical simulations as well as of the input and output dimension of the surrogate model can be extended to include several parameters.