A methodology for using long-period gratings and mold-filling simulations to minimize the intrusiveness of flow sensors in liquid composite molding

In liquid composite molding (LCM), a fiber preform is placed in the mold and a thermoset resin is injected into the closed mold cavity to occupy the spaces in between the fibers. A significant number of LCM parts are rejected on account of inadequate resin impregnation of the reinforcement preform during the mold filling stage. Hence, implementing sensors and active control can improve the cost efficiency of mold filling. In this paper, long-period grating sensors are utilized to monitor flow front progression. A methodology has been devised to compare the performances of different sensor configurations in the mold. Sensor performance evaluation is based on comparing the resin arrival times between the ideal mold filling situation and several simulated non-ideal scenarios. This methodology can be applied to any other discrete-sensor technology with an on/off response to the presence of resin and for other mold-filling anomalies. Filling simulations of a square plaque mold with a curved edge are used to illustrate the methodology.