Dirk Heider

Fiber Bragg grating sensors toward structural health monitoring in composite materials: challenges and solutions.

Nowadays, smart composite materials embed miniaturized sensors for structural health monitoring (SHM) in order to mitigate the risk of failure due to an overload or to unwanted inhomogeneity resulting from the fabrication process. Optical fiber sensors, and more particularly fiber Bragg grating (FBG) sensors, outperform traditional sensor technologies, as they are lightweight, small in size and offer convenient multiplexing capabilities with remote operation. They have thus been extensively associated to composite materials to study their behavior for further SHM purposes. This paper reviews the main challenges arising from the use of FBGs in composite materials. The focus will be made on issues related to temperature-strain discrimination, demodulation of the amplitude spectrum during and after the curing process as well as connection between the embedded optical fibers and the surroundings. The main strategies developed in each of these three topics will be summarized and compared, demonstrating the large progress that has been made in this field in the past few years.

Process and Performance Evaluation of the Vacuum-Assisted Process:

Vacuum-Assisted Resin Transfer Molding (VARTM) is widely used for large-scale composite manufacturing of civil and defense applications. Here, the infusion process reduces part costs due to a decrease in labor, material, and equipment expenses compared to other composite manufacturing techniques. However, in order to replace conventional manufacturing methods for aerospace-quality parts such as autoclave processing, the VARTM process repeatability and part quality must be improved. The Vacuum-Assisted Process (VAP) (Filsinger, J., Lorenz, T., Stadler, F. and Utecht, S. (2001). Method and Device for Producing Fiber-reinforced Components Using an Injection Method, German Patent WO 01/68353 A1.) developed and patented by EADS Deutschland uses a gas-permeable membrane to allow for uniform vacuum distribution and continuing degassing of the infused resin.W.L. Gore & Assoc. GmbH has developed a suitable membrane in co-operation with EADS. The membrane is placed over the fabric layers, sealed to the tool, and connected to the vent to allow uniform vacuum on the fabric surface. The VAP results in a more robust VARTM process that minimizes the potential for dry spot formation as well as lower void content and improved dimensional tolerances. This research quantifies the performance improvements and compares them to the Seemann Composite Resin Infusion Process (Seemann, William (1991). Plastic Transfer Molding Apparatus for the Production of Fiber Reinforced Plastic Structures, U.S. Patent, 5,052,906) (SCRIMP), the most common variation of the VARTM process.

Inter-layer thermal contact resistance evolution with the degree of intimate contact in the processing of thermoplastic composite laminates

This article focuses on the contact between layers in forming processes of composite laminate. The link between the degree of intimate contact and the consequent thermal contact resistance between layers is investigated. A hot plate forming process experiment allows to propose a relation and determine the missing parameter for APC2 thermoplastic prepreg composite. Besides the new proposed relation, this work showed that the internal thermal contact resistances in the laminate is significant. Therefore, thermal modeling of forming processes of composite laminate (such as automatic tape placement) should account for this phenomenon.

Electric time-domain reflectometry sensor for online flow sensing in liquid composite molding processing

This paper describes the development of a new sensor type for resin flow detection in liquid composite molding (LCM) processing. The sensor can be applied in any LCM process where lineal and high-resolution flow front detection is required, i.e. during prototyping or as a feedback sensor during flow front control. The operating principle of the embedded sensor is based on electrical time domain reflectometry (E-TDR). The system analyzes changes in the transmission line response during wet-out of the preform. The flat band transmission line, which is interrogated by E-TDR changes its dielectric properties when the resin is on or near the sensor resulting in reflection of the electrical signal. The signal is evaluated in the time-domain by mapping the areas of resin on the sensor. The study illustrates an analytical model to predict the TDR response for different resin systems, validates the accuracy and resolution of the system in a lab-scale set-up and implements the sensor in several different injection scenarios.

Experimental Investigation of the Controlled Atmospheric Pressure Resin Infusion (CAPRI) Process

Controlled atmospheric pressure resin infusion (CAPRI) is a variation of the vacuum-assisted resin transfer molding (VARTM) process. The CAPRI process increases the fiber volume fraction of the preform prior to infusion via debulking and applies a reduced pressure gradient during infusion to minimize thickness gradients during processing. This study experimentally investigates the effect of debulking and reduced pressure gradient on the incoming material parameters, process behavior and final dimensional tolerances. The effect of debulking on fabric permeability and compaction behavior has been investigated and shows a significant impact on the infusion time and final fiber volume fraction. Several E-glass plain weave preforms have been infused and flow, pressure and thickness data has been recorded and compared to traditional VARTM processing. A previously developed model uses the experimentally obtained permeability data and good agreement of the flow behavior is observed, the CAPRI process decreases thickness gradients to less than 1% while increasing fiber volume fraction by 5% in the composite part.

Application of a neural network to improve an automated thermoplastic tow-placement process

Abstract This study demonstrates the use of an on-line neural network to calculate process set points for PID controllers in a manufacturing process such as the automated thermoplastic tow-placement (ATP) technique. The set points are computed by the neural network so that the throughput is near maximum and a desired minimum quality is maintained. A novel neural network predictive scheme is developed to enable performance over a wide range of processing inputs. Process history can greatly affect the final part quality and, therefore, is an integral part of the method for determining the set points. The system is first trained and tested in simulation and then validated for the highly non-linear ATP process resulting in significantly improved process operation. The developed approach is applicable to many other manufacturing processes where process simulations exist and conventional control techniques are lacking.

High Through-Thickness Thermal Conductivity Composites Based on Three-Dimensional Woven Fiber Architectures

Composites based on laminates of uniaxial or biaxial fiber reinforcements exhibit low through-thickness thermal conductivity, due to low matrix thermal conductivity and the number of interfaces in the thermal path. For applications near heat-generating components, the use of laminate composites in the surrounding structure can be limited by this inability to transport heat through the thickness. Three-dimensional orthogonal weaving provides an efficient, cost-effective method of placing high thermal conductivity yarns in the through-thickness Z direction of a preform to yield structural composites with high through-thickness thermal conductivity and with in-plane strength or stiffness comparable to laminates. Three basic research efforts investigated the efficacy of this approach: 1) weaving trials to determine the ability to three-dimensional orthogonal weave pitch carbon fibers and plied copper wires in the Z direction of the preforms, 2) through-thickness thermal conductivity testing of composites based on three-dimensional preforms, and 3) thermal modeling to describe several of the phenomena observed during thermal conductivity tests. During the testing, composites based on the three-dimensional orthogonal preforms with Z fiber volume fractions of only 5.5% measured a 12-fold increase in through-thickness thermal conductivity over a laminate composite, 8.4 versus 0.7 W/m K.

Feedback control of the vacuum-assisted resin transfer molding (VARTM) process

The Vacuum Assisted Resin Transfer Molding (VARTM) technique is a liquid-molding process that offers the potential to significantly reduce fabrication costs for large-scale composite structures. The VARTM workcell is used to evaluate control strategies and sensors such as SMARTweave to provide feedback for an intelligent control system. Current VARTM systems lack automated control systems resulting in part to part variability. This research presents a continuously controlled vacuum actuator system and the influence of vacuum gradients on resin flow front control.

A neural network model-based open-loop optimization for the automated thermoplastic composite tow-placement system

This study demonstrates the use of on-line optimization algorithms to calculate optimum process set points for manufacturing processes such as the automated thermoplastic tow-placement (ATP) system. An in situ non-linear optimization technique based on artificial neural networks has been developed. This method is implemented in the ATP process and utilizes neural network-based process models to predict material quality as a function of process set points. The set points are computed by maximizing the throughput and maintaining a desired minimum quality. Process history can greatly affect the final part quality and, therefore, is an integral part of the optimization. The controller is validated for the highly non-linear ATP process and successfully predicts optimum processing parameters. The developed approach is applicable to many other manufacturing processes where process simulations exist and conventional control techniques are lacking.

Vacuum Assisted Resin Transfer Molding (VARTM) Process Incorporating Gravitational Effects: A Closed-form Solution

Vacuum assisted resin transfer molding (VARTM) is ideal for the manufacture of large-scale composite structures. However, gravitational effects on flow behavior can be significant in increasingly tall structures. In this study, an analytical solution incorporating the gravitational effects is developed to predict the flow and pressure distributions of uniform thickness preforms under vacuum infusion conditions. Injection scenarios of preforms of various lengths and inclination angles ranging from horizontal to vertical are studied. Nondimensional process parameters in terms of the resin fill time, mold angle, permeability, radius and length of injection tubes, and preform cross-sectional area for horizontal, downward, and upward injection scenarios are considered. The analytical results show good agreement with the experimental data collected in horizontal and vertical infusions. The parametric study provides insight into the design and optimization of the VARTM process for infusion of tall composite structures.