Myung-Keun Yoon

Effects of electrode degradation and solvent evaporation on the performance of ionic-polymer–metal composite sensors

An ionic-polymer–metal composite (IPMC) consists of an ionic polymer membrane and metallic electrodes plated on both surfaces. When it bends, a voltage is generated between the two electrodes across the membrane. Since it works not only in aqueous solution similar to in vivo but also in air, it can be used for embedded biomedical as well as surface-mounted sensors. The present study investigates the effect of solvent evaporation and mechanisms of electrode degradation of an IPMC when it is operated as a sensor. The output voltages and electrode resistances were measured with several cyclic bending motions applied on the sensor in both aqueous solution and air. There was a good correlation between the sensor voltage and the bending angle when the sensor was tested in aqueous solution. The sensor worked for a long time without attenuation in the output voltage in an aqueous solution. The output voltage, however, decreased rapidly when the sensor was operated in air. The results of resistance measurement showed that the electrode on the compressive side deformed more and generated more cracks than on the tensile side. Optical microscopic images taken on the electrode surfaces validated the results. The results provided very useful information needed to understand electrode degradation and solvent evaporation and to improve the performance of IPMC sensors.

Modeling VARTM Processes with Hybrid Media Incorporating Gravity Effects

Vacuum-assisted resin transfer molding (VARTM) processes are increasingly used in manufacturing scale-up composite applications. Accordingly, gravity can significantly influence the flow behavior in tall-structure composite manufacturing processes. The present study developed a closed-form analytic solution incorporating gravity effects with the equivalent parameter approach in order to predict the resin flow behavior in a tall structure resin infusion. A hybrid model was used that consists of thin distribution media and a fibrous preform. An analytic solution was developed and validated with experiments as well as numerical methods in terms of the resin flow front shape, lag length, and the flow front location with time for the horizontal, upward, and downward infusion cases. The flow front locations were monitored using time domain reflectometry sensors embedded in the fabric layers. The lag length was constant in the horizontal infusion case, but decreased and increased in the upward and downward infusion cases, respectively, as resin progressed. The downward infusion case showed the fastest fill time, which corresponds to the previous results using a homogenous model. However, the flow became unstable at a certain location where the local flow front speeds increased suddenly along the distribution media. These phenomena were not observed in a model with homogenous media but were observed in a model with hybrid media, only in the downward infusion cases. The analytic solution also identified the stable flow conditions with the mold angles. The results obtained in the present study can be used to estimate stable process conditions in designing VARTM processes for manufacturing large-scale tall composite structures.

Homogenous Modeling of VARTM Processes with Hybrid Layered Media

Numerical methods have been widely used to simulate vacuum assisted resin transfer molding (VARTM) processes to obtain optimum process parameters. Many VARTM parts have very large in-plane dimensions compared to the thickness. However, the incorporation of a highly permeable distribution media on the surface of a fibrous preform results in significant through thickness flow particularly at the flow front where large gradients can exist. In general, flow simulations that can model the distribution media as a discrete layer are needed, which, however, significantly increases the number of elements and thus computational costs in the numerical analyses. The present study introduces a homogenous preform system using equivalent porosity and permeability over the out-of-plane direction that retains the through-thickness flow characteristics in order to reduce complexity in modeling the distribution media in VARTM processes. First, a mass-average approach was developed to reduce the number of dimensions that needs to be modeled (e.g., 3-D is reduced to 2-D in-plane and 2-D cross section is reduced to a 1-D flow problem). Parametric studies were carried out over a reasonable range of the input parameters such as preform thickness, length, porosity, and permeability and showed limitations in using the mass average approach with homogenous models. Second, a reconstruction method was developed to predict accurately the flow pattern in the out-of-plane direction from the homogenous models. The flow pattern was successfully reconstructed using the flow data obtained from the homogenous model with an analytic solution of the flow front shape in the out-of-plane direction. Average flow front locations and the flow front patterns were investigated by numerical analyses for a few flow scenarios, which validated the present methods and quantified error levels in the resin flow pattern and resin fill time. The mass-average and reconstruction approaches successfully estimated the resin flow locations and patterns with respect to time and significantly reduced complexity in modeling complex geometries as well as computational costs.

Time domain reflectometry as a distributed strain sensor

Existing strain gages are mostly point sensors that measure local strains from a few discrete locations, while TDR sensor can interrogate distributed changes along the entire length of the sensor line. The present study investigates feasible applications of a new technique using TDR as a distributed strain sensor for structural health monitoring. First, a specially designed TDR sensor laid out on a substrate successfully measured distributed strains and detected a failure location when the substrate was under an increasing tensile load. Second, a TDR sensor spirally wound around a cylindrical tank measured a circumferential strain and detected a failure location on the tank surface when the tank was increasingly pressurized. The developed TDR monitoring technique shows great potential for real-time health monitoring of various critical structures such as bridge, aircraft, and aerospace applications.

Evaluation of Circuit Models for an IPMC Sensor to Effectively Detect the Bending Angles of a Body

Ionic Polymer-Metal Composite (IPMC) consists of an ion conductive membrane plated by metallic electrodes on both surfaces. When it bends, a voltage is generated between two electrodes. Since IPMC is flexible and thin, it can be easily mounted on the various surfaces of a body. Moreover, IPMC can produce output voltages without attenuation under large deflections. The present study investigates a sensor system using IPMC to effectively detect the bending angles applied on IPMC sensor. The paper evaluates existing R and C circuit models of IPMC and selects the best model for the detection of angles. The circuit models describe the relationship between input bending angles and output voltages. The identification of R and C values was performed by minimizing the error between the real output voltages and the simulated output voltages from the circuit models of IPMC sensor. Then the output signal of a sensor was fed into the inverse model of the identified model to reproduce the bending angles. In order to support the validation of the model, the output voltages from an arbitrary bending motion were also applied to the selected inverse model, which successfully reproduced the arbitrary bending motion. On-going work includes investigation of the selected circuit model to better understand the dynamics of the sensor as well as the relationships between electric and physical parameters of the sensor.© 2010 ASME