The research presented in this article focuses on a 9-m CX-100 wind turbine blade, designed by a team led by Sandia National Laboratories and manufactured by TPI Composites Inc. The key difference between the 9-m blade and baseline CX-100 blades is that this blade contains fabric wave defects of controlled geometry inserted at specified locations along the blade length. The defect blade was tested at the National Wind Technology Center at the National Renewable Energy Laboratory using a schedule of cycles at increasing load level until failure was detected. Researchers used digital image correlation, shearography, acoustic emission, fiber-optic strain sensing, thermal imaging, and piezoelectric sensing as structural health monitoring techniques. This article provides a comparison of the sensing results of these different structural health monitoring approaches to detect the defects and track the resultant damage from the initial fatigue cycle to final failure.

Digital image correlation (DIC) has been becoming increasingly popular as a means to perform structural health monitoring because of its full-field, non-contacting measurement ability. In this paper, 3D DIC techniques are used to identify the mode shapes of a wind turbine blade. The blade containing a handful of optical targets is excited at different frequencies using a shaker as well as a pluck test. The response is recorded using two PHOTRON TM high speed cameras. Time domain data is transferred to the frequency domain to extract mode shapes and natural frequencies using an Operational Modal Approach. A finite element model of the blade is also used to compare the mode shapes. Furthermore, a modal hammer impact test is performed using a more conventional approach with an accelerometer. A comparison of mode shapes from the photogrammetric, finite element, and impact test approaches are presented to show the accuracy of the DIC measurement approach.

We have created a multifunctional dry adhesive film with transferred vertically aligned carbon nanotubes (VA-CNTs). This unique VA-CNT film was fabricated by a multistep transfer process, converting the flat and uniform bottom of VA-CNTs grown on atomically flat silicon wafer substrates into the top surface of an adhesive layer. Unlike as-grown VA-CNTs, which have a nonuniform surface, randomly entangled CNT arrays, and a weak interface between the CNTs and substrates, this transferred VA-CNT film shows an extremely high coefficient of static friction (COF) of up to 60 and a shear adhesion force 30 times higher (12 N/cm) than that of the as-grown VA-CNTs under a very small preloading of 0.2 N/cm. Moreover, a near-zero normal adhesion force was observed with 20 mN/cm preloading and a maximum 100-μm displacement in a piezo scanner, demonstrating ideal properties for an artificial gecko foot. Using this unique structural feature and anisotropic adhesion properties, we also demonstrate effective removal and assembly of nanoparticles into organized micrometer-scale circular and line patterns by a single brushing of this flat and uniform VA-CNT film.

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