Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metric...Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks(DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.展开更多
Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Parti...Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Particularly, network component importance is addressed to express its significance in shaping the resilience performance of the whole system. Due to the intrinsic complexity of the problem, some idealized assumptions are exerted on the resilience-optimization problem to find partial solutions. This paper seeks to exploit the dynamic aspect of system resilience, i.e., the scheduling problem of link recovery in the post-disruption phase.The aim is to analyze the recovery strategy of the system with more practical assumptions, especially inhomogeneous time cost among links. In view of this, the presented work translates the resilience-maximization recovery plan into the dynamic decisionmaking of runtime recovery option. A heuristic scheme is devised to treat the core problem of link selection in an ongoing style.Through Monte Carlo simulation, the link recovery order rendered by the proposed scheme demonstrates excellent resilience performance as well as accommodation with uncertainty caused by epistemic knowledge.展开更多
An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage faciliti...An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.展开更多
Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calcula...Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.展开更多
Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneous...Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a jam.Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks.However,most real-world networks are directed.To fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks.We find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network dynamics.Due to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis behavior.In addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery processes.These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.展开更多
In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameter...In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameters.To this end,a method of Handover Parameters Adjustment for Conflict Avoidance(HPACA)is proposed.Considering the movement of users,HPCAC can dynamically adjust handover range to optimize the mobility load balancing.The movement of users is an important factor of handover,which has a dramatic impact on system performance.The numerical evaluation results show the proposed approach outperforms the existing method in terms of throughput,call blocking ratio,load balancing index,radio link failure ratio,ping-pong handover ratio and call dropping ratio.展开更多
Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy...Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.展开更多
To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transpor...To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transportation network(TN).First,the emergency response quickly increases the output of gas turbines(GTs)in the natural gas network(NGN),and responsively reconfigures the DN in microgrids,to maximize the amount of loads to be restored.The single-commodity flow model is adopted to construct spanning tree constraints.Then,in the second stage of energy storage recovery,mobile energy storage systems(MESSs)are deployed to cover the shortages of power demands,i.e.,to further restore the loads after evaluating the load recovery situation.The Floyd algorithm based dynamic traffic assignment(DTA)is selected to obtain the optimal path of the MESSs.In the third stage,the outputs of various post-disaster recovery measures are adjusted to achieve an economically optimized operation.Case studies demonstrate the effectiveness of the proposed dynamic post-disaster recovery strategy.展开更多
Title:A dual-parameter method for seismic resilience assessment of buildings Authors:LI Shuang;HU Binbin;LIU Wen;ZHAI Changhai Abstract:To quantify the seismic resilience of buildings,a method for evaluating functiona...Title:A dual-parameter method for seismic resilience assessment of buildings Authors:LI Shuang;HU Binbin;LIU Wen;ZHAI Changhai Abstract:To quantify the seismic resilience of buildings,a method for evaluating functional loss from the component level to the overall building is proposed,and the dual-parameter seismic resilience assessment method based on postearthquake loss and recovery time is improved.A three-level function tree model is established,which can consider the dynamic changes in weight coefficients of different category of components relative to their functional losses.Bayesian networks are utilized to quantify the impact of weather conditions,construction technology levels,and worker skill levels on component repair time.A method for determining the real-time functional recovery curve of buildings based on the component repair process is proposed.Taking a three-story teaching building as an example,the seismic resilience indices under basic earthquakes and rare earthquakes are calculated.The results show that the seismic resilience grade of the teaching building is comprehensively judged as GradeⅢ,and its resilience grade is more significantly affected by postearthquake loss.The proposed method can be used to predict the seismic resilience of buildings prior to earthquakes,identify weak components within buildings,and provide guidance for taking measures to enhance the seismic resilience of buildings.展开更多
基金financially supported by the National Natural Science Foundation of China (Grant No. 51779267)the Taishan Scholars Project (Grant No. tsqn201909063)+3 种基金the Science and Technology Support Plan for Youth Innovation of Universities in Shandong Province (Grant No.2019KJB016)the National Key Research and Development Program of China (Grant No. 2019YFE0105100)the Fundamental Research Funds for the Central Universitiesthe Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment (Grant No.20CX02301A)。
文摘Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks(DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.
基金supported by the National Natural Science Foundation of China(51479158)the Fundamental Research Funds for the Central Universities(WUT:2018III061GX)
文摘Prior research on the resilience of critical infrastructure usually utilizes the network model to characterize the structure of the components so that a quantitative representation of resilience can be obtained. Particularly, network component importance is addressed to express its significance in shaping the resilience performance of the whole system. Due to the intrinsic complexity of the problem, some idealized assumptions are exerted on the resilience-optimization problem to find partial solutions. This paper seeks to exploit the dynamic aspect of system resilience, i.e., the scheduling problem of link recovery in the post-disruption phase.The aim is to analyze the recovery strategy of the system with more practical assumptions, especially inhomogeneous time cost among links. In view of this, the presented work translates the resilience-maximization recovery plan into the dynamic decisionmaking of runtime recovery option. A heuristic scheme is devised to treat the core problem of link selection in an ongoing style.Through Monte Carlo simulation, the link recovery order rendered by the proposed scheme demonstrates excellent resilience performance as well as accommodation with uncertainty caused by epistemic knowledge.
基金supported by National Natural Science Foundation of China[grant number 51904316]provided by China University of Petroleum,Beijing[grant number2462021YJRC013,2462020YXZZ045]
文摘An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.
基金Supported by the Key Projection of Science and Technology Research of Ministry of Education of China (107057)the Science & Technology Fund for Students of Hohai University (K200803)
文摘Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.
基金supported by the National Natural Science Foundation of China(62172170)the Science and Technology Project of the State Grid Corporation of China(5100-202199557A-0-5-ZN).
文摘Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a jam.Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks.However,most real-world networks are directed.To fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks.We find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network dynamics.Due to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis behavior.In addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery processes.These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.
基金supported by the National Natural Science Foundation of China under Grant No.61071118the National Basic Research Program of China(973 Program)under Grant No.2012CB316004+1 种基金Special Fund of Chongqing Key Laboratory(CSTC)Chongqing Municipal Education Commission’s Science and Technology Research Project under Grant No.KJ111506
文摘In order to achieve dynamical optimization of mobility load balancing,we analyze the conflict between mobility load balancing and mobility robustness optimization caused by the improper operation of handover parameters.To this end,a method of Handover Parameters Adjustment for Conflict Avoidance(HPACA)is proposed.Considering the movement of users,HPCAC can dynamically adjust handover range to optimize the mobility load balancing.The movement of users is an important factor of handover,which has a dramatic impact on system performance.The numerical evaluation results show the proposed approach outperforms the existing method in terms of throughput,call blocking ratio,load balancing index,radio link failure ratio,ping-pong handover ratio and call dropping ratio.
文摘Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.
基金supported by the Science and Technology Project of the State Grid Corporation of China“Research on resilience technology and application foundation of intelligent distribution network based on integrated energy system”(No.52060019001H).
文摘To improve the resilience of distribution networks(DNs),a multi-stage dynamic recovery strategy is proposed in this paper,which is designed for post-disaster DN considering an integrated energy system(IES)and transportation network(TN).First,the emergency response quickly increases the output of gas turbines(GTs)in the natural gas network(NGN),and responsively reconfigures the DN in microgrids,to maximize the amount of loads to be restored.The single-commodity flow model is adopted to construct spanning tree constraints.Then,in the second stage of energy storage recovery,mobile energy storage systems(MESSs)are deployed to cover the shortages of power demands,i.e.,to further restore the loads after evaluating the load recovery situation.The Floyd algorithm based dynamic traffic assignment(DTA)is selected to obtain the optimal path of the MESSs.In the third stage,the outputs of various post-disaster recovery measures are adjusted to achieve an economically optimized operation.Case studies demonstrate the effectiveness of the proposed dynamic post-disaster recovery strategy.
文摘Title:A dual-parameter method for seismic resilience assessment of buildings Authors:LI Shuang;HU Binbin;LIU Wen;ZHAI Changhai Abstract:To quantify the seismic resilience of buildings,a method for evaluating functional loss from the component level to the overall building is proposed,and the dual-parameter seismic resilience assessment method based on postearthquake loss and recovery time is improved.A three-level function tree model is established,which can consider the dynamic changes in weight coefficients of different category of components relative to their functional losses.Bayesian networks are utilized to quantify the impact of weather conditions,construction technology levels,and worker skill levels on component repair time.A method for determining the real-time functional recovery curve of buildings based on the component repair process is proposed.Taking a three-story teaching building as an example,the seismic resilience indices under basic earthquakes and rare earthquakes are calculated.The results show that the seismic resilience grade of the teaching building is comprehensively judged as GradeⅢ,and its resilience grade is more significantly affected by postearthquake loss.The proposed method can be used to predict the seismic resilience of buildings prior to earthquakes,identify weak components within buildings,and provide guidance for taking measures to enhance the seismic resilience of buildings.
