Estimation of a stochastic spatio-temporal model of the flow-front dynamics with varying parameters

For control and monitoring purposes, knowledge of the current state of the flow-front in a vacuum assisted resin transfer moulding (VARTM) process is essential. The permeability of the medium and viscosity of the epoxy can change during the infusion process. Especially for online monitoring of the infusion process there is a need for a fast and fairly accurate, possibly virtual sensor system which can handle such parameter variations.

Stochastic-differential equations (SDEs) based estimation of the flow-front dynamics can offer a good trade-off between physics and data-driven estimators. In this paper, we analyze the effect of parameter variations on an SDE based spatio-temporal estimator of the flow-front dynamics in a VARTM process.