Luciana Arronche

Detection of spatially distributed damage in fiber-reinforced polymer composites:

This work describes a novel method of embedded damage detection within glass fiber–reinforced polymer composites. Damage detection is achieved by monitoring the spatially distributed electrical conductivity of a strain-sensitive multiwalled carbon nanotube thin film. First, thin films were spray-deposited directly upon glass fiber mats. Second, using electrical impedance tomography, the spatial conductivity distribution of the thin film was determined before and after damage-inducing events. The resolution of the sensor was determined by drilling progressively larger holes in the center of the composite specimens, and the corresponding electrical impedance tomography response was measured by recording the current–voltage data at the periphery of the monitored composite sample. In addition, the sensitivity to damage occurring at different locations in the composite was also investigated by comparing electrical impedance tomography spatial conductivity maps obtained for specimens with sets of holes drilled at different locations in the sensing area. Finally, the location and severity of damage from low-velocity impact events were detected using the electrical impedance tomography method. The work presented in this study indicates a paradigm shift in the available possibilities for structural health monitoring of fiber-reinforced polymer composites.

Influence of carbon nanotube on the piezoresistive behavior of multiwall carbon nanotube/polymer composites

The role of the physical properties of multiwall carbon nanotubes on the strain-sensing piezoresistive behavior of multiwall carbon nanotube/polymer composites is systematically studied using three types of multiwall carbon nanotubes as fillers of a brittle thermosetting (vinyl ester) and a tough thermoplastic (polypropylene) polymers under quasi-static tensile loading. Two of the three multiwall carbon nanotubes investigated have similar length, aspect ratio, structural ordering, and surface area, while the third group contains longer multiwall carbon nanotubes with higher structural ordering. The results indicate that longer multiwall carbon nanotubes with higher structural ordering yield higher piezoresistive sensitivity, and therefore are better suited as sensors of elastic and plastic strains of polymer composites. The highest gage factor achieved was approximately 24 and corresponded to the plastic zone of multiwall carbon nanotube/polypropylene composites with the longest nanotubes.

FATIGUE DAMAGE IDENTIFICATION IN COMPOSITE STRUCTURES THROUGH ULTRASONICS AND WAVELET TRANSFORM SIGNAL PROCESSING

This is an investigation on the damage behavior of fiberglass/epoxy specimens with embedded piezoelectrics under axial tensile fatigue. The specimen’s local and global damage states are complicated by the specimen’s own stretching under loading, which varies as a function of damage. A signal processing technique based on wavelet transforms is presented: denoised signals are processed with Gabor wavelet transforms, and the area of one of the contours is tracked throughout the fatigue life.

Evaluation of the Damage Detection Characteristics of Electrical Impedance Tomography

In the United States, many civil, aerospace, and military aircraft are nearing the end of their service life. Many of these service life predictions were determined by models that were created at the time of the design of the structure, possibly decades ago. As a precaution, these structures are inspected on a regular basis with techniques that tend to be expensive and laborious, such as tear-down inspections of aircraft. To complicate matters, new complex materials have been incorporated in recent structures to take advantage of their desirable properties, but these materials sustain damage in a manner that is different from that of past monolithic materials. One example is fiber-reinforced polymer (FRP) composites, which are heterogeneous, direction-dependent, and tend to manifest damage internal to their laminate structure, thus making the detection of this damage nearly impossible. For these reasons, numerous groups have focused on developing sensors that can be applied to or embedded within these structures to detect this damage. Some of the most promising of these approaches include using piezoelectric materials as passive or active ultrasonic sensors and actuators, fiber optic-based sensors to measure strain and detect cracking, and carbon nanotube-based sensors that can detect strain and cracking. These are mostly point-based sensors that are accurate at the location of application but require interpolative methods to ascertain the structural health elsewhere on the structure. To conduct direct damage detection across a structure, we have coupled the ability to deposit a carbon nanotube thin film across large substrates with a spatially distributed electrical conductivity measurement methodology called electrical impedance tomography. As indicated by previous research on carbon nanotube thin films, the electrical conductivity of these films changes when subjected to strain or become damaged. Our structural health monitoring strategy involves monitoring for changes in electrical conductivity across an applied CNT thin film, which would indicate damage. In this work, we demonstrate the ability of the Electrical Impedance Tomography (EIT) methodology to detect, locate, size, and determine severity of damage from impact events subjected to glass fiber-reinforced polymer composites. This will demonstrate the value and effectiveness of this next-generation structural health monitoring approach.Copyright

Conductivity-Based Damage Detection in Carbon Fiber Composites

Fiber-reinforced polymer (FRP) composites have become a primary structural material in many new structures, particularly in the aerospace, wind turbine, automobile, and marine industries, due to their higher strength-to-weight ratios, corrosion resistance, and ease of manufacturing. However, these composite materials have complex damages modes that are different from typical monolithic metallic alloys, such as delamination, fiber breakage, matrix cracking, and fiber-matrix debonding. These avenues of damage tend to manifest internally to the composite structure, making them nearly invisible to visual inspection. Several damage detection approaches have been introduced for the purpose of in situ non-destructive evaluation (NDE) of composites; however, many of these approaches require complex analysis methods, data interpolation for achieving spatial sensing, and/or embedding invasive sensors into the composites themselves. To allow for widespread implementation of a next-generation NDE approach for composites, an easily discernible, highly visual, and fast approach that does not adversely affect the structural performance of the composite laminate is needed. This study introduces the use of a spatially distributed electrical conductivity distribution mapping method called electrical impedance tomography (EIT). EIT reconstructs a material’s 2D or 3D electrical conductivity within a series of boundary electrodes. A 100 mA current is injected between two opposing electrodes while the adjacent differential voltages are measured at the remaining electrodes; this process is repeated for all opposing electrode pairs. Using a linear reconstruction algorithm, changes in electrical conductivity are spatially resolved and plotted for easy detection, localization, and evaluation of damage. This approach is validated by applying EIT to a set of carbon fiber-reinforced polymer composite laminates. First, damage has been simulated in composite parts by selectively removing portions of the structure and then verifying that EIT has captured this occurrence. After validation of the EIT method, pristine composite laminates have been subjected to low velocity impact damage. Before and after impact EIT readings have been taken. The differential conductivity reconstruction is presented. This work demonstrates the value of adopting electrical impedance tomography for in situ NDE of FRP composites.Copyright