Bayesian Inversion in Resin Transfer Moulding #

Michael Causon

Poster session

Abstract #

We study the Bayesian inverse problem of inferring the permeability of a porous medium within the context of a moving boundary framework motivated by Resin Transfer Moulding (RTM), one of the most commonly used processes for manufacturing fibre-reinforced composite materials. During the injection of resin in RTM, our aim is to update our probabilistic knowledge of the permeability of the material by inverting pressure measurements. Key to this is the development of fast Gaussian approximations to the posterior distribution of permeability.