Highly-instrumented particles (i.e. “Smart Rocks”) were included in monodisperse dry granular landslide experiments to quantify the collisional nature of such flows, and to investigate the influence of collisional flow on the mobility of landslides. The total number of particles comprising a constant source volume of 0.4 m3 was varied by filling the volume with monodisperse particles of nominal diameters of 3 mm, 6 mm, 13 mm, or 25 mm. Successively raising the total particle count resulted in flows that were increasingly thick relative to the respective particle size. Raw resultant acceleration data from the embedded smart rock sensors indicate that for each increase in grain size, there were increases in both the magnitude and frequency of particle collisions. Lidar-generated point clouds of the landslide deposits indicated that increases in mobility and spreading, compared using differences in travel angle, were directly proportional to increases in collisional activity. By changing the size of the landslide particles from 3 mm to 25 mm, the travel angle at the gravity centre (αg) was observed to decrease from 27.8° to 25.3° (Δαg = - 9.0 %) and the Fahrböschung angle (α) was observed to decrease from 25.0° to 21.4° (Δα = -14.4 %).
Research quality data from geotechnical tests conducted at the designated National Geotechnical Experimentation Sites (NGES) are currently available in a database accessible through the Internet. The data include general site information, stratigraphy, laboratory and in situ test details. The database is structured to follow the rules of Relations Database Management Systems (RDBMS). The database resides in a Unix based Sun Solaris server and the database engine is Sybase RDBMS. The NGES database user interface query application has been developed for the Internet using Java as the programming language and runs under any Internet capable browser. The application uses Java applets to communicate with the database server. The interface comes with user-friendly query capabilities along with graphic display of various results in tabular and chart forms. The user community includes researchers, students, and practicing engineers in geotechnical and geo-related fields.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.