Heterogeneous-structured Cu samples composed of coarse-grained(CG) and ultrafine-grained(UFG) domains with a transitional interface were fabricated by friction stir processing, in order to investigate the effect of in...Heterogeneous-structured Cu samples composed of coarse-grained(CG) and ultrafine-grained(UFG) domains with a transitional interface were fabricated by friction stir processing, in order to investigate the effect of interface constraint on the yielding and fracture behaviors. Tensile test revealed that the synergetic strengthening induced by elastic/plastic interaction between incompatible domains increases with increasing the area of constraint interface. The strain distribution near interface and the fracture morphology were characterized using digital image correlation technique and scanning electron microscopy, respectively. Fracture dimples preferentially formed at the interface, possibly due to extremely high triaxial stress and strain accumulation near the interface. Surprisingly, the CG domain was fractured by pure shear instead of the expected voids growth caused by tensile stress.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
基金Projects(11672195,51301092) supported by the National Natural Science Foundation of ChinaProject(2016JQ0047) supported by Sichuan Youth Science and Technology Foundation,China
文摘Heterogeneous-structured Cu samples composed of coarse-grained(CG) and ultrafine-grained(UFG) domains with a transitional interface were fabricated by friction stir processing, in order to investigate the effect of interface constraint on the yielding and fracture behaviors. Tensile test revealed that the synergetic strengthening induced by elastic/plastic interaction between incompatible domains increases with increasing the area of constraint interface. The strain distribution near interface and the fracture morphology were characterized using digital image correlation technique and scanning electron microscopy, respectively. Fracture dimples preferentially formed at the interface, possibly due to extremely high triaxial stress and strain accumulation near the interface. Surprisingly, the CG domain was fractured by pure shear instead of the expected voids growth caused by tensile stress.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
