TY - JOUR
T1 - Sensing Mechanism and Real-Time Computing for Granular Materials
AU - Liu, Shushu
AU - Huang, Hai
AU - Qiu, Tong
AU - Shen, Shihui
N1 - Publisher Copyright:
© 2018 American Society of Civil Engineers.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - The discrete element method (DEM) has been widely used to study the mechanical behavior of granular materials. However, potential error accumulation over the required large number of time steps due to the explicit time integration in DEM simulations may undermine the simulation accuracy. In this paper, a computing scheme based on real-time data fusion between a sensing mechanism and traditional DEM is developed and investigated. The developed sensing mechanism and real-time (SMART) computing consists of: (1) real-time data acquisition of particle kinematics through a wireless instrumentation called SmartRocks that are embedded at discrete locations in a granular assemblage, and (2) a built-in data-fusion-based algorithm using the Kalman filter to integrate the prediction generated by DEM and the measurements reported by SmartRocks. The performance of the SMART computing algorithm is investigated by simulating a series of ball collision experiments consisting of two-ball center-to-center, two-ball off-center, and multiball collisions. It is concluded that SMART computing can improve the accuracy of DEM simulations. The results of this study suggest that the location and number of SmartRocks, whose recordings are fused into DEM simulations to recondition the particle movements, are important to the accuracy of SMART computing.
AB - The discrete element method (DEM) has been widely used to study the mechanical behavior of granular materials. However, potential error accumulation over the required large number of time steps due to the explicit time integration in DEM simulations may undermine the simulation accuracy. In this paper, a computing scheme based on real-time data fusion between a sensing mechanism and traditional DEM is developed and investigated. The developed sensing mechanism and real-time (SMART) computing consists of: (1) real-time data acquisition of particle kinematics through a wireless instrumentation called SmartRocks that are embedded at discrete locations in a granular assemblage, and (2) a built-in data-fusion-based algorithm using the Kalman filter to integrate the prediction generated by DEM and the measurements reported by SmartRocks. The performance of the SMART computing algorithm is investigated by simulating a series of ball collision experiments consisting of two-ball center-to-center, two-ball off-center, and multiball collisions. It is concluded that SMART computing can improve the accuracy of DEM simulations. The results of this study suggest that the location and number of SmartRocks, whose recordings are fused into DEM simulations to recondition the particle movements, are important to the accuracy of SMART computing.
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U2 - 10.1061/(ASCE)CP.1943-5487.0000769
DO - 10.1061/(ASCE)CP.1943-5487.0000769
M3 - Article
AN - SCOPUS:85046153444
SN - 0887-3801
VL - 32
JO - Journal of Computing in Civil Engineering
JF - Journal of Computing in Civil Engineering
IS - 4
M1 - 04018023
ER -