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 seismic reliability evaluation of lifeline networks has received considerable attention and been widely studied. In this paper, on the basis of an original recursive decomposition algorithm, an improved analytical...The seismic reliability evaluation of lifeline networks has received considerable attention and been widely studied. In this paper, on the basis of an original recursive decomposition algorithm, an improved analytical approach to evaluate the seismic reliability of large lifeline systems is presented. The proposed algorithm takes the shortest path from the source to the sink of a network as decomposition policy. Using the Boolean laws of set operation and the probabilistic operation principal, a recursive decomposition process is constructed in which the disjoint minimal path set and the disjoint minimal cut set are simultaneously enumerated. As the result, a probabilistic inequality can be used to provide results that satisfy a prescribed error bound. During the decomposition process, different from the original recursive decomposition algorithm which only removes edges to simplify the network, the proposed algorithm simplifies the network by merging nodes into sources and removing edges. As a result, the proposed algorithm can obtain simpler networks. Moreover, for a network owning s-independent components in its component set, two network reduction techniques are introduced to speed up the proposed algorithm. A series of case studies, including an actual water distribution network and a large urban gas system, are calculated using the proposed algorithm. The results indicate that the proposed algorithm provides a useful probabilistic analysis method for the seismic reliability evaluation of lifeline networks.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Natural Science Funds for the Innovative Research Group of China Under Grant No.50621062
文摘The seismic reliability evaluation of lifeline networks has received considerable attention and been widely studied. In this paper, on the basis of an original recursive decomposition algorithm, an improved analytical approach to evaluate the seismic reliability of large lifeline systems is presented. The proposed algorithm takes the shortest path from the source to the sink of a network as decomposition policy. Using the Boolean laws of set operation and the probabilistic operation principal, a recursive decomposition process is constructed in which the disjoint minimal path set and the disjoint minimal cut set are simultaneously enumerated. As the result, a probabilistic inequality can be used to provide results that satisfy a prescribed error bound. During the decomposition process, different from the original recursive decomposition algorithm which only removes edges to simplify the network, the proposed algorithm simplifies the network by merging nodes into sources and removing edges. As a result, the proposed algorithm can obtain simpler networks. Moreover, for a network owning s-independent components in its component set, two network reduction techniques are introduced to speed up the proposed algorithm. A series of case studies, including an actual water distribution network and a large urban gas system, are calculated using the proposed algorithm. The results indicate that the proposed algorithm provides a useful probabilistic analysis method for the seismic reliability evaluation of lifeline networks.