Bob Minaie

Effects of variation in autoclave pressure, temperature, and vacuum-application time on porosity and mechanical properties of a carbon fiber/epoxy composite

This article presents results from investigation of the effects of variation in autoclave pressure, temperature, and vacuum-application time on porosity, hot/wet (H/W) and room temperature/dry (RT/D) short beam shear (SBS) strength, and failure mechanism of a commercial carbon fiber/epoxy prepreg, Cycom IM7/977-2 unidirectional tape. Fourteen cure cycles were designed to study a wide range of curing pressures, curing temperatures, and two different vacuum-application durations, including vacuum vented at recommended pressure and vacuum held throughout the cure cycle. The results showed that the SBS strength did not vary significantly over a relatively wide range of curing temperatures and pressures if vacuum was vented at recommended curing pressure; however, after a certain point, a decreasing trend in the SBS strength was observed by reducing the curing temperature and pressure. The C-scan images of panels cured with the vacuum held throughout the cure cycles revealed presence of a high-porosity cross-shaped defect at the center of the panels. The observed defect became larger as the curing pressure decreased. The correlation between the SBS strength and the void content was studied using theoretical models and experimental data. The investigation of the failure modes for each panel showed a change in both the H/W and the RT/D failure mechanism as a result of variation in curing temperature and pressure.

Remote Monitoring of Resin Transfer Molding Processes by Distributed Dielectric Sensors

Feed-forward adaptive control of resin transfer molding (RTM) processes is crucial for producing a high yield of usable parts for industrial applications. The enabling technique for this process is non-invasive monitoring of the fill-front position and the degree of cure of the resin as it is injected into the mold. Successful implementation of a sensing system capable of meeting these criteria will result in a high yield of composite parts that can be used for the next generation of aircraft. This article articulates the possibility of a hybrid sensing system for multiparameter monitoring during RTM processes. It addresses the fundamental engineering trade-offs between penetration depth and signal strength, discussing how to account for fringing electric field (FEF) effects present in the system. FEF effects hinder the measurement accuracy of the sensor system. This article describes how these effects are addressed using a mapping algorithm that is developed using numerical simulations of the experimental setup. The experimental setup utilizes a rectangular RTM tool and a water-glycerin mixture which simulates mechanical properties of epoxy resins, prior to cure. Modeling of the FEF effects helps to achieve high measurement accuracy of the fill front location.

Thermal, rheological, and mechanical properties of a polymer composite cured at different isothermal cure temperatures

Thermal, rheological, and mechanical properties of a commercial carbon fiber epoxy prepreg, Cycom 977-2 UD, were obtained for isothermal cure temperatures ranging from 149°C to 182°C. For each cure profile, an encapsulated-sample rheometer (ESR) was used to measure the storage modulus. Each ESR cure profile was followed by the glass transition temperature (Tg) test. The degree of cure (α) during cure and the heat of reaction of the prepreg were obtained using a differential scanning calorimeter (DSC). Combined loading compression (CLC) and short-beam shear (SBS) tests were performed to obtain compressive properties and SBS strength, respectively. It was observed that the compressive properties did not vary significantly for the studied isothermal cure temperatures; likewise, the compressive failure mode was the same for all the CLC specimens. However, the SBS strength for the specimens cured at 149°C was approximately 10% less than that of those cured at isothermal cure temperatures ranging from 160°C to 182°C. Further, the failure mode of the SBS specimens cured at 149°C was also different from other specimens. The storage modulus of the ESR sample cured at 149°C also showed a 10% decrease compared to other ESR samples. The SBS strength exhibited a good correlation with the storage modulus and a weak correlation with Tg and α.

Adaptive Control of Filling Pattern in Resin Transfer Molding Process

During the Resin Transfer Molding (RTM) process, the filling pattern is strongly affected by race-tracking phenomenon and this usually leads to dry spot formation at the end of the filling stage and results in defective parts. This situation can be alleviated by placing air vents at the locations of the Last Point to Fill (LPF), where dry spots usually form. However, due to the variation of the race-tracking effects, the LPF location does not remain in the same position during RTM batch cycle production. Dry spots can still form and the part is still scraped. In order to ensure that the LPF location always coincides with the predetermined vent during RTM batch cycle production, an adaptive control strategy based on a model reference adaptation system that can regulate the LPF location during the RTM filling stage is proposed, to adjust the inlet pressures on-line. Multiport flow is simplified as many individual one-dimensional ‘spine’ flows and each ‘spine’ extends from the gate to the vent along the short path. The spine flow is controlled independently by adjusting the pressure of the related inlet. The control input is the distance between the inlet and the flow front along the spines, and the reference model of the flow is that the resin is driven by a uniform velocity from the gate to the vent along the spine. The proposed adaptive control has the capability to adapt to high levels of system disturbances. The proposed adaptive control is tested numerically by incorporating the control algorithm into a RTM time-implicit filling simulation. The resulting simulations show that the proposed control strategy can eliminate the dry spot formation under a wide range of situations resulting from the variations in the race-tracking effects.

A methodology to determine permeability distribution of a preform in resin transfer molding process

This article presents a scheme that directly calculates permeability distribution of a preform during the RTM process. The measured filling front locations as well as the corresponding inlet conditions are used in the proposed scheme to calculate the permeability distribution that also takes into account race-tracking phenomenon. The proposed scheme employs a numerical optimization algorithm to minimize a cost function that leads to the permeability field of the preform. Time-step-independent RTM filling algorithm is utilized as a computational kernel to generate the cost function for the subsequent minimization. Numerical development of the proposed scheme is discussed in this article. In addition, the proposed scheme is applied to several test problems involving a variety of spatial permeability distribution of the preform including a situation that involves race-tracking phenomena.

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