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- W4386157665 abstract "Rockfalls can often pose a significant risk to the public if protective designs do not properly account for block movement downslope and onto infrastructure facilities. Assessing these hazards is challenging, especially as current empirical and computational methods for predicting trajectories of falling blocks generally do not include the contribution associated with rotational behavior. Research undertaken at the University of New Hampshire, USA, over the last decade has led to the development of Smart Rock (SR) sensors inserted in natural rocks to evaluate these events from the perspective of the falling rock. The latest SRs consist of 3D printed capsules 58.0 mm in length and 25.4 mm in diameter, equipped with a ±400 g and a ±16 g 3-axis accelerometer, a ±4000 dps high-rate gyroscope, and an altimeter. Approximately 80 field experiments conducted in New Hampshire and Vermont provided SR data on rockfall at ten different sites. The Smart Rock data allowed more in-depth evaluations of accelerations, rotation rates, and modes of motion with precise time intervals, which cannot be easily captured in video recording systems or other instrumentation techniques. Such measurements are essential to improve our understanding and modeling of rockfall events for more economical and safer design of protective systems." @default.
- W4386157665 created "2023-08-26" @default.
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- W4386157665 date "2023-08-25" @default.
- W4386157665 modified "2023-09-27" @default.
- W4386157665 title "Rockfall motion using a Smart Rock sensor" @default.
- W4386157665 doi "https://doi.org/10.1139/cgj-2022-0599" @default.
- W4386157665 hasPublicationYear "2023" @default.
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