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Exploring and designing two-dimensional (2D) nanomaterials for armor-piercing protection has become a research focus. Here, by molecular dynamics simulation, we revealed that the ultralight monolayer covalent organic framework (COF), one kind of novel 2D crystalline polymer, possesses superior impactresistant capability under high-velocity impact. The calculated specific penetration energy is much higher than that of other traditional impact-resistant materials, such as steel, poly(methyl methacrylate), Kevlar, etc. It was found that the hexagonal nanopores integrated by polymer chains have large deformation compatibility resulting from flexible torsion and stretching, which can remarkably contribute to the energy dissipation. In addition, the deformable nanopores can effectively restrain the crack propagation, enable COF to resist multiple impacts. This work uncovers the extreme dynamic responses of COF under highvelocity impact and provides theoretical guidance for designing superstrong 2D polymer-based crystalline nanomaterials.

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When the occupant density of buildings is large enough, evacuees are prone to congestion during emergency evacuation, which leads to the extension of the overall escape time. Especially for multi-exit buildings, it’s a challenging problem to afford an effective evacuation plan. In this paper, a novel evacuation planning algorithm applied to multi-exit buildings is proposed, which is based on an indoor route network model. Firstly, evacuees are grouped by their location proximity, then all groups are approximately equally classified into several evacuation zones, each of which has only one safe exit. After that, all evacuation groups in the same zone are sorted by their shortest path length, then the time window of each evacuation group occupying the safe exit is calculated in turn. In the case of congestion at the safe exit, the departure time of each evacuation group is delayed in its arrival order. The objectives of the proposed algorithm include minimizing the total evacuation time of all evacuees, the travel time of each evacuee, avoiding traffic congestion, balancing traffic loads among different exits, and achieving high computational efficiency. Case studies are conducted to examine the performance of our algorithm. The influences of group number, group size, evacuation speed on the total evacuation time are discussed on a single-exit network, and that of partitioning methods and evacuation density on the performance and applicability in different congestion levels are also discussed on a multi-exit network. Results demonstrate that our algorithm has a higher efficiency and performs better for evacuations with a large occupant density.

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