This paper numerically investigates particle saltation in a turbulent channel flow having a rough bed consisting of 2–3 layers of densely packed spheres.In this study,we combined three the state-of-the-art technologi...This paper numerically investigates particle saltation in a turbulent channel flow having a rough bed consisting of 2–3 layers of densely packed spheres.In this study,we combined three the state-of-the-art technologies,i.e.,the direct numerical simulation of turbulent flow,the combined finite-discrete element modelling of the deformation,movement and collision of the particles,and the immersed boundary method for the fluid-solid interaction.Here we verify our code by comparing the flow and particle statistical features with the published data and then present the hydrodynamic forces acting on a particle together with the particle coordinates and velocities,during a typical saltation.We found strong correlation between the abruptly decreasing particle stream-wise velocity and the increasing vertical velocity at collision,which indicates that the continuous saltation of large grain-size particles is controlled by collision parameters such as particle incident angle,local rough bed packing arrangement,and particle density,etc.This physical process is different from that of particle entrainment in which turbulence coherence structures play an important role.Probability distribution functions of several important saltation parameters and the relationships between them are presented.The results show that the saltating particles hitting the windward side of the bed particles are more likely to bounce off the rough bed than those hitting the leeside.Based on the above findings,saltation mechanisms of large grain-size particles in turbulent channel flow are presented.展开更多
Due to the scattered nature of the network,data transmission in a dis-tributed Mobile Ad-hoc Network(MANET)consumes more energy resources(ER)than in a centralized network,resulting in a shorter network lifespan(NL).As...Due to the scattered nature of the network,data transmission in a dis-tributed Mobile Ad-hoc Network(MANET)consumes more energy resources(ER)than in a centralized network,resulting in a shorter network lifespan(NL).As a result,we build an Enhanced Opportunistic Routing(EORP)protocol architecture in order to address the issues raised before.This proposed routing protocol goal is to manage the routing cost by employing power,load,and delay to manage the routing energy consumption based on theflooding of control pack-ets from the target node.According to the goal of the proposed protocol techni-que,it is possible to manage the routing cost by applying power,load,and delay.The proposed technique also manage the routing energy consumption based on theflooding of control packets from the destination node in order to reduce the routing cost.Control packet exchange between the target and all the nodes,on the other hand,is capable of having an influence on the overall efficiency of the system.The EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adja-cent nodes for each node in the routing route as part of the routing path discovery process,which occurs during control packet transmission.While control packet transmission is taking place during the routing path discovery process,the EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adjacent nodes for each node in the routing.Also included is a simulation of these protocols in order to evaluate their performance across a wide range of packet speeds using Constant Bit Rate(CBR).When the packet rate of the CBR is 20 packets per second,the results reveal that the EORP-MCCND is 0.6 s quicker than the state-of-the-art protocols,according to thefindings.Assuming that the CBR packet rate is 20 packets per second,the EORP-MCCND achieves 0.6 s of End 2 End Delay,0.05 s of Routing Overhead Delay,120 s of Network Lifetime,and 展开更多
基金supported by a Marie Curie International Incoming Fellowship within the seventh European Community Framework Programme(Grant No.PIIF-GA-2009-236457)the financial support of the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(Grant No.51321065)+2 种基金Programme of Introducing Talents of Discipline to Universities(Grant No.B14012)National Natural Science Foundation of China(Grant Nos.50809047 and 51009105)Natural Science Foundation of Tianjin(Grant No.12JCQNJC02600)
文摘This paper numerically investigates particle saltation in a turbulent channel flow having a rough bed consisting of 2–3 layers of densely packed spheres.In this study,we combined three the state-of-the-art technologies,i.e.,the direct numerical simulation of turbulent flow,the combined finite-discrete element modelling of the deformation,movement and collision of the particles,and the immersed boundary method for the fluid-solid interaction.Here we verify our code by comparing the flow and particle statistical features with the published data and then present the hydrodynamic forces acting on a particle together with the particle coordinates and velocities,during a typical saltation.We found strong correlation between the abruptly decreasing particle stream-wise velocity and the increasing vertical velocity at collision,which indicates that the continuous saltation of large grain-size particles is controlled by collision parameters such as particle incident angle,local rough bed packing arrangement,and particle density,etc.This physical process is different from that of particle entrainment in which turbulence coherence structures play an important role.Probability distribution functions of several important saltation parameters and the relationships between them are presented.The results show that the saltating particles hitting the windward side of the bed particles are more likely to bounce off the rough bed than those hitting the leeside.Based on the above findings,saltation mechanisms of large grain-size particles in turbulent channel flow are presented.
文摘Due to the scattered nature of the network,data transmission in a dis-tributed Mobile Ad-hoc Network(MANET)consumes more energy resources(ER)than in a centralized network,resulting in a shorter network lifespan(NL).As a result,we build an Enhanced Opportunistic Routing(EORP)protocol architecture in order to address the issues raised before.This proposed routing protocol goal is to manage the routing cost by employing power,load,and delay to manage the routing energy consumption based on theflooding of control pack-ets from the target node.According to the goal of the proposed protocol techni-que,it is possible to manage the routing cost by applying power,load,and delay.The proposed technique also manage the routing energy consumption based on theflooding of control packets from the destination node in order to reduce the routing cost.Control packet exchange between the target and all the nodes,on the other hand,is capable of having an influence on the overall efficiency of the system.The EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adja-cent nodes for each node in the routing route as part of the routing path discovery process,which occurs during control packet transmission.While control packet transmission is taking place during the routing path discovery process,the EORP protocol and the Multi-channel Cooperative Neighbour Discovery(MCCND)protocol have been designed to detect the cooperative adjacent nodes for each node in the routing.Also included is a simulation of these protocols in order to evaluate their performance across a wide range of packet speeds using Constant Bit Rate(CBR).When the packet rate of the CBR is 20 packets per second,the results reveal that the EORP-MCCND is 0.6 s quicker than the state-of-the-art protocols,according to thefindings.Assuming that the CBR packet rate is 20 packets per second,the EORP-MCCND achieves 0.6 s of End 2 End Delay,0.05 s of Routing Overhead Delay,120 s of Network Lifetime,and
