Kuang-Ting Hsiao

A Numerical Study of Integrated Direct Cure Kinetics Characterization and Control for Resin Transfer Molding (RTM)

In Resin Transfer Molding (RTM), the fiber preform is first placed inside a mold cavity and is subsequently impregnated with liquid resin. After mold filling, the resin starts to cure and bind the fiber preform into a solid composite part. The cure cycle will affect the residual stress built during RTM and must be controlled. Traditionally, the cure cycle control is achieved through three steps: offline resin cure kinetics characterization, offline cure cycle optimization, and mold temperature control. Different from other traditional cure cycle control approaches, this paper presents an investigation to achieve an integrated cure kinetics characterization-control system by combining a newly developed direct cure kinetics characterization method with online cure cycle optimization. A methodology to seamlessly combine these components for a practicable online cure characterization-control system will be presented and demonstrated by a numerical case study. The accuracy and reliability of this methodology will be examined and discussed based on the results of the numerical case study.Copyright

Optimization of Spine Sensor Location in Resin Ttransfer Molding

Resin Transfer Molding (RTM) is a manufacturing process to produce polymer composite parts. RTM is comprised of four stages: 1) cutting and placing of the fiber mats (preform) inside a mold, 2) resin injection, 3) curing of the part, and 4) demolding of the hardened part. Resin injection is the most critical stage in RTM and it can be affected by unpredictable parameters such as preform permeability variations. These variations can produce unrepeatable filling patterns where the Last Point to Fill (LPF) may not coincide with the exit vent location. Failure to completely wet the fibers inside the mold can cause dry spots which are major defects that usually require the part to be scrapped. In order to overcome the uncertainties in the filling stage, adaptive control can be used to monitor and regulate the flow front such that the LPF coincides with the vent location. Recently, the development of sensors has allowed continuous sensing of the flow front in a straight line. Such sensors can be placed between the injection gates and the vent. The location of these sensors can affect adaptive control and the resulting filling pattern and, therefore, the final quality of the part. The work presented in this paper uses a search algorithm to find the optimal location for the sensors. The results of this optimization study can be used to enhance future control algorithms and, therefore, can lead to a more successful RTM process.Copyright

Enhancement of Dimensional Stability of Polymer Composites Manufacturing Using Carbon Nanofibers

Process induced residual stress arises in polymer composites as a result of resin shrinkage during cure cycle. When a shell-like composite part is demolded, these residual stresses result in change of dimensions such as spring-in, which is a phenomenon that the enclosed angles of the composite part are reduced due to process-induced residual stress. To have good precision in the composite part, the dimensional instability of enclosed angles must be controlled and/or compensated. The traditional approach is to estimate the spring-in and consequently correct the mold geometry to counterbalance the predicted dimensional instability. The success of such mold design practice relies on the past experience or by costly trial and error approach. In this paper, we present a new approach to reduce the spring-in by using Carbon Nanofibers (CNF). CNF have remarkable physical and mechanical properties and have excellent dimensional stability and hence may be useful in improving the dimensional stability of polymer composites. In this experimental study, we dispersed different fractions of CNF into fiberglass/polyester composite parts with corner angles and compared their spring-in angles after the composite parts were demolded. The results show that the CNF can effectively restrain the undesired deformation and improve the dimensional stability of polymer composites during manufacturing process.Copyright