The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the ...The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the reaction dynamics of energetic materials,its utility is often constrained to capturing only fundamental reaction events and species information,thereby limiting mechanistic investigations of complex reaction pathways.To elucidate the topological features of energetic material reaction networks and identify critical reaction pathways with high fidelity,this study presents ReacNetwork-an advanced large-scale reaction network analysis methodology that synergistically integrates complex network theory with molecular simulation techniques.Specifically,we have developed a multi-dimensional feature screening protocol based on node centrality metrics and K-shell decomposition algorithms.Takingα-Hexahydro-1,3,5-trinitro-1,3,5-triazine(α-RDX)as the subject,we successfully constructed a comprehensive high-temperature thermal decomposition reaction network consisting of 1,134 distinct chemical species and 3,626 elementary reactions.Through systematic application of community detection algorithms and global topological feature extraction techniques,we achieved effective dimensionality reduction and successfully identified the dominant reaction pathway within theα-RDX thermal decomposition network.The computational results not only validate the well-established initial reaction mechanism dominated by N-NO2 homolytic bond cleavage,but also provide unprecedented visualization ofα-RDX framework ring-opening dynamics and subsequent radical chain propagation networks.展开更多
The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the contro...The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.展开更多
This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywo...This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywords after indexing national R＆D information in Korea （human resources, project and outcome） and applying expertise calculation algorithm. In consideration of the characteristics of national R＆D information, weight values have been selected. Then, expertise points were calculated by applying weighted values. In addition, joint research and collaborative relations were implemented in a knowledge map format through network analysis using national R＆D information.展开更多
Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the s...Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.展开更多
基金support from the National Natural Science Foundation of China(Grant No.22275018).
文摘The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the reaction dynamics of energetic materials,its utility is often constrained to capturing only fundamental reaction events and species information,thereby limiting mechanistic investigations of complex reaction pathways.To elucidate the topological features of energetic material reaction networks and identify critical reaction pathways with high fidelity,this study presents ReacNetwork-an advanced large-scale reaction network analysis methodology that synergistically integrates complex network theory with molecular simulation techniques.Specifically,we have developed a multi-dimensional feature screening protocol based on node centrality metrics and K-shell decomposition algorithms.Takingα-Hexahydro-1,3,5-trinitro-1,3,5-triazine(α-RDX)as the subject,we successfully constructed a comprehensive high-temperature thermal decomposition reaction network consisting of 1,134 distinct chemical species and 3,626 elementary reactions.Through systematic application of community detection algorithms and global topological feature extraction techniques,we achieved effective dimensionality reduction and successfully identified the dominant reaction pathway within theα-RDX thermal decomposition network.The computational results not only validate the well-established initial reaction mechanism dominated by N-NO2 homolytic bond cleavage,but also provide unprecedented visualization ofα-RDX framework ring-opening dynamics and subsequent radical chain propagation networks.
基金Project(61104106)supported by the National Natural Science Foundation of ChinaProject(201202156)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(LJQ2012100)supported by the Program for Liaoning Excellent Talents in University(LNET),China
文摘The stability analysis and stabilization problems of the wireless networked control systems(WNCSs) with signal transmission deadbands were considered. The deadbands were respectively set up at the sensor to the controller and the controller to the actor sides in the WNCS, which were used to reduce data transmission, furthermore, to decrease the network collision and node energy consumption. Under the consideration of time-varying delays and signal transmission deadbands, the model for the WNCS was presented. A novel Lyapunov functional which took full advantages of the network factors was exploited. Meanwhile, new stability analysis and stabilization conditions for the WNCS were proposed, which described the relationship of the delay bounds, the transmission deadband bounds and the system stability. Two examples were used to demonstrate the effectiveness of the proposed methods. The results show that the proposed approach can guarantee asymptotical stability of the system and reduce the data transmission effectively.
基金Project(N-12-NM-LU01-C01) supported by Construction of NTIS (National Science & Technology Information Service) Program Funded by the National Science & Technology Commission (NSTC), Korea
文摘This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywords after indexing national R＆D information in Korea （human resources, project and outcome） and applying expertise calculation algorithm. In consideration of the characteristics of national R＆D information, weight values have been selected. Then, expertise points were calculated by applying weighted values. In addition, joint research and collaborative relations were implemented in a knowledge map format through network analysis using national R＆D information.
基金This research was funded by National Natural Science Foundation of China(grant number 61473311,70901075)Natural Science Foundation of Beijing Municipality(grant number 9142017)military projects funded by the Chinese Army.
文摘Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge.However,one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge.In this paper,we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics,integrating conceptual analysis,conceptual modeling,quantitative modeling and simulation implementation.We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition,thus classifying the related battle damage knowledge logically.Then,we construct the conceptual model of influencing factors of battle damage by using Entity-Relations hip approach,thus describing their interactions reasonably.Subsequently,we extract the important influencing factors by using social network analysis,thus evaluating their importance quantitatively and further clarifying the elements of simulation.Finally,we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input,and obtain simulation model output,i.e.,new battle damage laws knowledge,thus verifying feasibility and effectiveness of the proposed method.The results show that this method can be used to support human decision-making and action.
