Evaluation of Impulse Attenuation by Football Helmets in the Frequency Domain.

Design of helmets used in contact sports has been driven by the necessity of preventing severe head injuries. Manufacturing standards and pass or fail grading systems ensure protective headgear built to withstand large impacts, but design standards do no account for impacts resulting in subconcussive episodes and the effects of cumulative impacts on its user. Thus, it is important to explore new design parameters, such as the frequency-domain measures of transmissibility and mechanical impedance that are based on energy absorption from a range of impact loads. Within the experimentally determined frequency range of interest (FROI), transmissibilities above unity were found in the 0-40 Hz range with the magnitude characteristics varying considerably with impact location. A similar variability with location was observed for the mechanical impedance, which ranged from 9 N/m to 50 N/m. Additional research is required to further understand how changes in the components or materials of the components will affect the performance of helmets, and how they may be used to reduce both transmissibility and dynamic impedance.

Data Acquisition Protocol for Determining Embedded Sensitivity Functions.

The effectiveness of many structural health monitoring techniques depends on the placement of sensors and the location of input forces. Algorithms for determining optimal sensor and forcing locations typically require data, either simulated or measured, from the damaged structure. Embedded sensitivity functions provide an approach for determining the best available sensor location to detect damage with only data from the healthy structure. In this video and manuscript, the data acquisition procedure and best practices for determining the embedded sensitivity functions of a structure is presented. The frequency response functions used in the calculation of the embedded sensitivity functions are acquired using modal impact testing. Data is acquired and representative results are shown for a residential scale wind turbine blade. Strategies for evaluating the quality of the data being acquired are provided during the demonstration of the data acquisition process.

Wind turbine blade shear web disbond detection using rotor blade operational sensing and data analysis.

A wind turbine blade's structural dynamic response is simulated and analysed with the goal of characterizing the presence and severity of a shear web disbond. Computer models of a 5 MW offshore utility-scale wind turbine were created to develop effective algorithms for detecting such damage. Through data analysis and with the use of blade measurements, a shear web disbond was quantified according to its length. An aerodynamic sensitivity study was conducted to ensure robustness of the detection algorithms. In all analyses, the blade's flap-wise acceleration and root-pitching moment were the clearest indicators of the presence and severity of a shear web disbond. A combination of blade and non-blade measurements was formulated into a final algorithm for the detection and quantification of the disbond. The probability of detection was 100% for the optimized wind speed ranges in laminar, 30% horizontal shear and 60% horizontal shear conditions.