Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analy...Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.展开更多
The reliability evaluation of a multistate network is primarily based on d-minimal paths/cuts(d-MPs/d-MCs).However,being a nondeterminism polynomial hard(NP-hard)problem,searching for all d-MPs is a rather challenging...The reliability evaluation of a multistate network is primarily based on d-minimal paths/cuts(d-MPs/d-MCs).However,being a nondeterminism polynomial hard(NP-hard)problem,searching for all d-MPs is a rather challenging task.In existing implicit enumeration algorithms based on minimal paths(MPs),duplicate d-MP candidates may be generated.An extra step is needed to locate and remove these duplicate d-MP candidates,which costs significant computational effort.This paper proposes an efficient method to prevent the generation of duplicate d-MP candidates for implicit enumeration algorithms for d-MPs.First,the mechanism of generating duplicate d-MP candidates in the implicit enumeration algorithms is discussed.Second,a direct and efficient avoiding-duplicates method is proposed.Third,an improved algorithm is developed,followed by complexity analysis and illustrative examples.Based on the computational experiments comparing with two existing algorithms,it is found that the proposed method can significantly improve the efficiency of generating d-MPs for a particular demand level d.展开更多
In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS...In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS with crash fault agents is performed. Resilience is used to analyze the processes of cascading failure and self-repair of UAS. Through simulation studies, we reveal the pivotal relationship between resilience, the swarm size, and the percentage of failed agents.The simulation results show that the swarm size does not affect the cascading failure process but has much influence on the process of self-repair and the final performance of the swarm.The results also reveal a tipping point exists in the swarm. Meanwhile, we get a counter-intuitive result that larger-scale UAS loses more resilience in the case of a small percentage of failed individuals, suggesting that the increasing swarm size does not necessarily lead to high resilience. It is also found that the temporal degree failure strategy performs much more harmfully to the resilience of swarm systems than the random failure. Our work can provide new insights into the mechanisms of swarm collapse, help build more robust UAS, and develop more efficient failure or protection strategies.展开更多
基金supported by the National Natural Science Foundation of China(72271242)Hunan Provincial Natural Science Foundation of China for Excellent Young Scholars(2022JJ20046).
文摘Cutting off or controlling the enemy’s power supply at critical moments or strategic locations may result in a cascade failure,thus gaining an advantage in a war.However,the exist-ing cascading failure modeling analysis of interdependent net-works is insufficient for describing the load characteristics and dependencies of subnetworks,and it is difficult to use for model-ing and failure analysis of power-combat(P-C)coupling net-works.This paper considers the physical characteristics of the two subnetworks and studies the mechanism of fault propaga-tion between subnetworks and across systems.Then the surviv-ability of the coupled network is evaluated.Firstly,an integrated modeling approach for the combat system and power system is predicted based on interdependent network theory.A heteroge-neous one-way interdependent network model based on proba-bility dependence is constructed.Secondly,using the operation loop theory,a load-capacity model based on combat-loop betweenness is proposed,and the cascade failure model of the P-C coupling system is investigated from three perspectives:ini-tial capacity,allocation strategy,and failure mechanism.Thirdly,survivability indexes based on load loss rate and network sur-vival rate are proposed.Finally,the P-C coupling system is con-structed based on the IEEE 118-bus system to demonstrate the proposed method.
基金supported by the National Natural Science Foundation of China(71701207)the Science and Technology on Reliability&Environmental Engineering Laboratory(6142004004-2)the Science and Technology Commission of the CMC(2019-JCJQ-JJ-180)。
文摘The reliability evaluation of a multistate network is primarily based on d-minimal paths/cuts(d-MPs/d-MCs).However,being a nondeterminism polynomial hard(NP-hard)problem,searching for all d-MPs is a rather challenging task.In existing implicit enumeration algorithms based on minimal paths(MPs),duplicate d-MP candidates may be generated.An extra step is needed to locate and remove these duplicate d-MP candidates,which costs significant computational effort.This paper proposes an efficient method to prevent the generation of duplicate d-MP candidates for implicit enumeration algorithms for d-MPs.First,the mechanism of generating duplicate d-MP candidates in the implicit enumeration algorithms is discussed.Second,a direct and efficient avoiding-duplicates method is proposed.Third,an improved algorithm is developed,followed by complexity analysis and illustrative examples.Based on the computational experiments comparing with two existing algorithms,it is found that the proposed method can significantly improve the efficiency of generating d-MPs for a particular demand level d.
基金This work was supported by the Science and Technology on Reliability&Environmental Engineering Laboratory(6142004004-2)the Science Technology Commission of the CMC(2019-JCJQ-JJ-180,ZZKY-YX-10-3).
文摘In this paper, we focus on the failure analysis of unmanned autonomous swarm(UAS) considering cascading effects. A framework of failure analysis for UAS is proposed.Guided by the framework, the failure analysis of UAS with crash fault agents is performed. Resilience is used to analyze the processes of cascading failure and self-repair of UAS. Through simulation studies, we reveal the pivotal relationship between resilience, the swarm size, and the percentage of failed agents.The simulation results show that the swarm size does not affect the cascading failure process but has much influence on the process of self-repair and the final performance of the swarm.The results also reveal a tipping point exists in the swarm. Meanwhile, we get a counter-intuitive result that larger-scale UAS loses more resilience in the case of a small percentage of failed individuals, suggesting that the increasing swarm size does not necessarily lead to high resilience. It is also found that the temporal degree failure strategy performs much more harmfully to the resilience of swarm systems than the random failure. Our work can provide new insights into the mechanisms of swarm collapse, help build more robust UAS, and develop more efficient failure or protection strategies.
