A new methodology for race-tracking detection and criticality in resin transfer molding process using pressure sensors

Abstract

In this study, a simplified cost effective simulation-based methodology is proposed to assist manufacturing engineers in the design and development phase of the resin transfer molding process. Race-tracking is unavoidable in the resin transfer molding and can lead to entrapment of air pockets, which results in parts being discarded as scrap. A purely numerical methodology is presented to distinguish between the critical and non-critical race-tracking scenarios, that will guide the design and production engineers plan an efficient and effective manufacturing strategy. The detection methodology is based on computing the pressure evolution with time during the injection process. The novelty relies on the superimposition of the computed pressure gradient maps that reveals unsuspected common features in the numerous race-tracking cases investigated in the various geometries of increasing complexity considered. The pressure sensors are meant to detect and evaluate different race-tracking scenarios and their level of criticality. The minimum number and locations of pressure sensors arise directly from the highest pressure gradient zones for simple geometries. Sensors placement guidelines are introduced for a simple rectangular shape, then this information is used to qualitatively apply the guidelines to parts of more complex shapes. A general rule that all parts, no matter how complex, can be considered as a combination of simpler ones is presented. Furthermore, a new failure criterion is proposed based on the flow patterns that highlights the likely flow patterns to entrap voids.

Direct numerical simulation of infusion and flow-front tracking in materials with heterogeneous permeability using a pressure mapping sensor

“…The experimental pressure field versus time, obtained with the pressure mapping sensor P exp , was also used to characterise the permeability of the preform. Assuming a uniform effective anisotropic homogeneous permeability, given by equation (6), the pressure field P mod can be modelled analytically as developed in section Flow modelling. Using a classical inverse method, the longitudinal and transverse in-plane permeabilities k x and k y can be inferred by minimising the difference between P mod and P exp min kx, ky ðÞ X t,x,y P mod x, y, t ðÞ À P exp x, y, t…”

“…Advanced software (such as PAM-RTM, LIMS, or Moldex3D) can handle process anomalies, such as race-tracking if the preform does not fit the mould properly, but an estimate for permeability in the race-tracking region is required by the simulation to predict whether any dry spots will arise during infusion. [4][5][6][7] Variability is often present in composite preforms, and may result in entrapment of air during filling that leads to dry spots in the final part. Previous studies have addressed material variability in discontinuous mats.…”

“…Nonetheless, it requires an in-situ tracking of the flow front inside the mould. Use of transparent mould 4,5,22 is a solution that cannot be scaled up to industrial processes, whereas dielectric 21,23 or pressure 6 sensors are usually point measurements only giving sparse processing information. Electric sensors do not provide pressure data at the measurement location, 24 whereas thin film pressure mapping sensors provide highdensity pressure measurements with minimal intrusion to the preform.…”

Hurdles and limitations for design of a radial permeameter conforming to the benchmark requirements

“…Predicted permeability values are commonly validated by comparison with experimental results since experimentally measured permeability reflects the unpredictability of the real environment conditions, namely the characteristic variability of the fibrous reinforcements that are difficult to simulate. For that reason, the accuracy of a validation depends on the quality of the input parameters such as the fabrics compaction response or the preform permeability in a real process (Siddig et al, 2018). While accurate experimental permeability data is relevant for the achievement of satisfactory simulation results, this is also difficult to obtain.…”

Comparison of in-plane resin transfer molding and vacuum-assisted resin transfer molding ‘effective’ permeabilities based on mold filling experiments and simulations

“…Process modeling and flow simulations of RTM and VARTM have been developed that predict the resin flow patterns, pressure distribution, and mold filling time that can assist in designing inlet and vents and optimize the process to produce parts without voids or dry-spots. For RTM, over the last three decades, several researchers have developed RTM process models and simulations, 2–7 based on constant material properties (no change in thickness, fiber volume fraction or permeability) during resin infusion and have validated them with RTM experiments. These simulations are very efficient and can predict mold filling for parts with many complex features and are being used by industry in their prototype development cycle.…”