Spacer grids play an important role in pressurized water reactor（PWR） fuel assembly in that they have significant influence on the thermal-hydraulic characteristics of the reactor core.But so far,the numerical studi...Spacer grids play an important role in pressurized water reactor（PWR） fuel assembly in that they have significant influence on the thermal-hydraulic characteristics of the reactor core.But so far,the numerical studies are performed without regarding dimple and spring of spacer grids,just considering mixing vane.Moreover,these studies use k-ε turbulence model without considering the suitability of the other turbulence models upon the different spacer grids flow.A study is carried out to understand the 3-D single-phase flow in AFA-2G 5×5 rod bundles with spacer grids based on numerical method.In order to investigate the suitability of different turbulence models,k-ε model and k-ω model,the influence of different parts of spacer grid on the fluid flow is also predicted.By using second-order upwind scheme,hybrid grids technique,and improved SIMPLEC algorithm,the Reynolds averaged mass conservation and momentum conservation equations are solved,and the pressure and velocity field of flow are obtained.The numerical simulation results are compared with experiment results and the agreement is satisfactory.The simulation results show the influences of the spring,dimple and mixing vane,and the different characteristics of the k-ε model and k-ω model.Comparing with the experiment results,the simulation results suggest that the k-ω model is suitable for the simulation of the rod bundle flow with spacer grids;the spring and dimple are the main causes of the pressure loss in the spacer grid channel.The friction coefficient of the channel with spring and dimple is 1.5 times the coefficient of the channel with the vane.These results are beneficial to enhance the simulation ability of spacer grids flow and optimization design ability of spaces grid.展开更多
针对静态和动态救援场景下的多无人机协同任务调度问题,提出基于密度的噪声应用空间聚类-一致性包算法(density-based spatial clustering of applications with noise-consensus-based bundle algorithm,DBSCAN-CBBA)。首先,针对任务...针对静态和动态救援场景下的多无人机协同任务调度问题,提出基于密度的噪声应用空间聚类-一致性包算法(density-based spatial clustering of applications with noise-consensus-based bundle algorithm,DBSCAN-CBBA)。首先,针对任务执行阶段存在的场景不确定以及无人机携带物资载荷限制等问题,建立了一种更为符合救援实际的多任务分配模型。然后,优化了一致性包算法的任务包构建结构以提高算法效率和搜索最优解的能力。第1阶段通过基于密度聚类算法生成候选任务集合,并通过随机方式构建非候选任务集合;第2阶段通过无人机之间的通信,消解它们因独立构建任务包而产生的冲突。最后,将该算法分别应用于静态和实时动态任务分配场景。仿真实验结果表明,该算法可较为高效地找到合理的任务分配方案。展开更多
This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors pr...This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors propose a consensus-based algorithm in distributed case, that is, the double- clock consensus-based K-means algorithm （DCKA）. With mild connectivity conditions, the authors show convergence of DCKA to guarantee a distributed solution to the clustering problem, even though the network topology is time-varying. Moreover, the authors provide experimental results on vari- ous clustering datasets to illustrate the effectiveness of the fully distributed algorithm DCKA, whose performance may be better than that of the centralized K-means algorithm.展开更多
In this paper, we present a distributed consensus-based algorithm to solve the social welfare maximization problem. This is one of typical problems of distributed energy management in smart grid. In this problem, we c...In this paper, we present a distributed consensus-based algorithm to solve the social welfare maximization problem. This is one of typical problems of distributed energy management in smart grid. In this problem, we consider not only the generator and demand, but also the transmission losses which make the feasibility set of the formulated problem a non-convex set. In solving this issue, we find a noticeable result that the primal problem has the same solution with a new convex optimization problem by getting the utmost out of the implied term in practice. Considering the general communication topology among generators and demands, we first design a finite step algorithm to make each generator and demand know the information of parameters of others.Then, we design a distributed algorithm and also prove the optimality and convergence of the proposed algorithm. Finally, the convergence and optimality are examined through extensive simulations.展开更多
Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribut...Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals(SDGs)for urban agglomerations.However,studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking.We pronovel integrated modeling framework that integrates the CLUES,InVEST,SOM,and GWR approaches to address the complex relationship between ecosystem services over a long“past-present-future”time series.We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales.In the future scenario,the water yield(WY),habitat quality(HQ),and soil conservation(SC)show similar spatial patterns,with comparable spatial grids,while carbon stock(CS)remains predominantly unchanged and the ecological protection scenario(EPS)improves more significantly.The high-synergy regions are mainly distributed in bundle 4,and most of the trade-off regions appear in bundles 1 and 2.Over the last 30 years,all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations,which are 15%higher in the Guangxi Beibu Gulf(GBG)than in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).From 2020 to 2035,the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario(EPS).In particular,bundles 3 and 4 are significantly improved.This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.展开更多
A decentralized task planning algorithm is proposed for heterogeneous unmanned aerial vehicle(UAV)swarm with different capabilities.The algorithm extends the consensus-based bundle algorithm(CBBA)to account for a more...A decentralized task planning algorithm is proposed for heterogeneous unmanned aerial vehicle(UAV)swarm with different capabilities.The algorithm extends the consensus-based bundle algorithm(CBBA)to account for a more realistic and complex environment.The extension of the algorithm includes handling multi-agent task that requires multiple UAVs collaboratively completed in coordination,and consideration of avoiding obstacles in task scenarios.We propose a new consensus algorithm to solve the multi-agent task allocation problem and use the Dubins algorithm to design feasible paths for UAVs to avoid obstacles and consider motion constraints.Experimental results show that the CBBA extension algorithm can converge to a conflict-free and feasible solution for multi-agent task planning problems.展开更多
基金supported by National Key Laboratory of Bubble Physics and Natural Circulation of China(Grant No. 51482040105CB0103)
文摘Spacer grids play an important role in pressurized water reactor（PWR） fuel assembly in that they have significant influence on the thermal-hydraulic characteristics of the reactor core.But so far,the numerical studies are performed without regarding dimple and spring of spacer grids,just considering mixing vane.Moreover,these studies use k-ε turbulence model without considering the suitability of the other turbulence models upon the different spacer grids flow.A study is carried out to understand the 3-D single-phase flow in AFA-2G 5×5 rod bundles with spacer grids based on numerical method.In order to investigate the suitability of different turbulence models,k-ε model and k-ω model,the influence of different parts of spacer grid on the fluid flow is also predicted.By using second-order upwind scheme,hybrid grids technique,and improved SIMPLEC algorithm,the Reynolds averaged mass conservation and momentum conservation equations are solved,and the pressure and velocity field of flow are obtained.The numerical simulation results are compared with experiment results and the agreement is satisfactory.The simulation results show the influences of the spring,dimple and mixing vane,and the different characteristics of the k-ε model and k-ω model.Comparing with the experiment results,the simulation results suggest that the k-ω model is suitable for the simulation of the rod bundle flow with spacer grids;the spring and dimple are the main causes of the pressure loss in the spacer grid channel.The friction coefficient of the channel with spring and dimple is 1.5 times the coefficient of the channel with the vane.These results are beneficial to enhance the simulation ability of spacer grids flow and optimization design ability of spaces grid.
文摘针对静态和动态救援场景下的多无人机协同任务调度问题,提出基于密度的噪声应用空间聚类-一致性包算法(density-based spatial clustering of applications with noise-consensus-based bundle algorithm,DBSCAN-CBBA)。首先,针对任务执行阶段存在的场景不确定以及无人机携带物资载荷限制等问题,建立了一种更为符合救援实际的多任务分配模型。然后,优化了一致性包算法的任务包构建结构以提高算法效率和搜索最优解的能力。第1阶段通过基于密度聚类算法生成候选任务集合,并通过随机方式构建非候选任务集合;第2阶段通过无人机之间的通信,消解它们因独立构建任务包而产生的冲突。最后,将该算法分别应用于静态和实时动态任务分配场景。仿真实验结果表明,该算法可较为高效地找到合理的任务分配方案。
基金supported by the National Key Research and Development Program of China under Grant No.2016YFB0901902the National Natural Science Foundation of China under Grant Nos.61573344,61333001,61733018,and 61374168
文摘This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors propose a consensus-based algorithm in distributed case, that is, the double- clock consensus-based K-means algorithm （DCKA）. With mild connectivity conditions, the authors show convergence of DCKA to guarantee a distributed solution to the clustering problem, even though the network topology is time-varying. Moreover, the authors provide experimental results on vari- ous clustering datasets to illustrate the effectiveness of the fully distributed algorithm DCKA, whose performance may be better than that of the centralized K-means algorithm.
基金supported by the Science and Technology Project of State Grid Zhejiang Electric Power Co.Ltd.(Grant No.5211JY17000P)the Fundamental Research Funds for the Central Universities(Grant No.2242019K40111)+1 种基金the National Natural Science Foundation of China(Grant No.61673107)the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence(Grant No.BM2017002)
文摘In this paper, we present a distributed consensus-based algorithm to solve the social welfare maximization problem. This is one of typical problems of distributed energy management in smart grid. In this problem, we consider not only the generator and demand, but also the transmission losses which make the feasibility set of the formulated problem a non-convex set. In solving this issue, we find a noticeable result that the primal problem has the same solution with a new convex optimization problem by getting the utmost out of the implied term in practice. Considering the general communication topology among generators and demands, we first design a finite step algorithm to make each generator and demand know the information of parameters of others.Then, we design a distributed algorithm and also prove the optimality and convergence of the proposed algorithm. Finally, the convergence and optimality are examined through extensive simulations.
基金National Natural Science Foundation of China,No.U21A2022,No.U1901219,No.42071393,No.42101369。
文摘Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals(SDGs)for urban agglomerations.However,studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking.We pronovel integrated modeling framework that integrates the CLUES,InVEST,SOM,and GWR approaches to address the complex relationship between ecosystem services over a long“past-present-future”time series.We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales.In the future scenario,the water yield(WY),habitat quality(HQ),and soil conservation(SC)show similar spatial patterns,with comparable spatial grids,while carbon stock(CS)remains predominantly unchanged and the ecological protection scenario(EPS)improves more significantly.The high-synergy regions are mainly distributed in bundle 4,and most of the trade-off regions appear in bundles 1 and 2.Over the last 30 years,all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations,which are 15%higher in the Guangxi Beibu Gulf(GBG)than in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).From 2020 to 2035,the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario(EPS).In particular,bundles 3 and 4 are significantly improved.This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.
文摘A decentralized task planning algorithm is proposed for heterogeneous unmanned aerial vehicle(UAV)swarm with different capabilities.The algorithm extends the consensus-based bundle algorithm(CBBA)to account for a more realistic and complex environment.The extension of the algorithm includes handling multi-agent task that requires multiple UAVs collaboratively completed in coordination,and consideration of avoiding obstacles in task scenarios.We propose a new consensus algorithm to solve the multi-agent task allocation problem and use the Dubins algorithm to design feasible paths for UAVs to avoid obstacles and consider motion constraints.Experimental results show that the CBBA extension algorithm can converge to a conflict-free and feasible solution for multi-agent task planning problems.
