Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters ...Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters of rockfall movement is critical for understanding motion patterns and effectively preventing and controlling rockfall hazards.In this study,a monitoring system consisting of selfdeveloped inertial navigation equipment,high-speed cameras,and an unmanned aerial vehicle was used to conduct onsite motion tests involving four differently shaped rock specimens on three types of slopes(bedrock,detritus,and clast bedding).The selfdeveloped inertial navigation system integrated a highdynamic-range accelerometer(±400 g)and a shockresistant gyroscope(±4000°/s),capable of robustly collecting data during the test.The data collected from these tests were processed to extract key kinematic parameters such as velocity,trajectory,restitution coefficients,and friction coefficients.The test results demonstrated that the inertial navigation system accurately recorded the acceleration and angular velocity of the rocks during motion,with these measurements closely aligning with the field data.The normal and tangential restitution coefficients were found to be influenced primarily by the slope material and impact angle,with higher normal restitution coefficients observed for low-angle impacts.The normal restitution coefficients ranged from 0.35 to 0.86,whereas the tangential restitution coefficients ranged from 0.46 to 0.91,depending on the slope materials.Additionally,the sliding friction coefficient was calculated to be between 0.66 and 0.78,whereas the rolling friction coefficient for the slab-shaped specimen was determined to be 0.53.These findings provide valuable data for improving the accuracy of rockfall trajectory predictions and the design of protective structures.展开更多
The velocity of a particle detector in granular flow can be regarded as the combination of rolling and sliding velocities.The study of the contribution of rolling velocity and sliding velocity provides a new explanati...The velocity of a particle detector in granular flow can be regarded as the combination of rolling and sliding velocities.The study of the contribution of rolling velocity and sliding velocity provides a new explanation to the relative motion between the detector and the local granular flow.In this study,a spherical detector using embedded inertial navigation technology is placed in the chute granular flow to study the movement of the detector relative to the granular flow.It is shown by particle image velocimetry(PIV)that the velocity of chute granular flow conforms to Silbert’s formula.And the velocity of the detector is greater than that of the granular flow around it.By decomposing the velocity into sliding and rolling velocity,it is indicated that the movement of the detector relative to the granular flow is mainly caused by rolling.The rolling detail shown by DEM simulation leads to two potential mechanisms based on the position and drive of the detector.展开更多
基金supported by Guizhou Provincial Basic Research Program(Natural Science,Grant No.QKHJC-ZK[2022]YB075)the National Natural Science Foundation of China(Grant No.42067046)+2 种基金the Guizhou Provincial Program on Commercialization of Scientific and Technological Achievements(N0.QKHCG-LH2024-ZD025)the Science and Technology Planning Project of Guiyang City(Grant No.ZKHT[2023]13-10)Undergraduate Training Program for Innovation and Entrepreneurship of Guizhou Province(Project No.S202110657053)。
文摘Rockfall kinematic characteristics exhibit significant randomness and are influenced by factors such as rock mass properties,slope morphology,impact angle,and slope materials.Accurately determining the key parameters of rockfall movement is critical for understanding motion patterns and effectively preventing and controlling rockfall hazards.In this study,a monitoring system consisting of selfdeveloped inertial navigation equipment,high-speed cameras,and an unmanned aerial vehicle was used to conduct onsite motion tests involving four differently shaped rock specimens on three types of slopes(bedrock,detritus,and clast bedding).The selfdeveloped inertial navigation system integrated a highdynamic-range accelerometer(±400 g)and a shockresistant gyroscope(±4000°/s),capable of robustly collecting data during the test.The data collected from these tests were processed to extract key kinematic parameters such as velocity,trajectory,restitution coefficients,and friction coefficients.The test results demonstrated that the inertial navigation system accurately recorded the acceleration and angular velocity of the rocks during motion,with these measurements closely aligning with the field data.The normal and tangential restitution coefficients were found to be influenced primarily by the slope material and impact angle,with higher normal restitution coefficients observed for low-angle impacts.The normal restitution coefficients ranged from 0.35 to 0.86,whereas the tangential restitution coefficients ranged from 0.46 to 0.91,depending on the slope materials.Additionally,the sliding friction coefficient was calculated to be between 0.66 and 0.78,whereas the rolling friction coefficient for the slab-shaped specimen was determined to be 0.53.These findings provide valuable data for improving the accuracy of rockfall trajectory predictions and the design of protective structures.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11972212,12072200,and 12002213)。
文摘The velocity of a particle detector in granular flow can be regarded as the combination of rolling and sliding velocities.The study of the contribution of rolling velocity and sliding velocity provides a new explanation to the relative motion between the detector and the local granular flow.In this study,a spherical detector using embedded inertial navigation technology is placed in the chute granular flow to study the movement of the detector relative to the granular flow.It is shown by particle image velocimetry(PIV)that the velocity of chute granular flow conforms to Silbert’s formula.And the velocity of the detector is greater than that of the granular flow around it.By decomposing the velocity into sliding and rolling velocity,it is indicated that the movement of the detector relative to the granular flow is mainly caused by rolling.The rolling detail shown by DEM simulation leads to two potential mechanisms based on the position and drive of the detector.
