Research on optimal emergency evacuation path for mine water inrush based on dynamic D-K algorithm
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摘要:
矿井水害发生后，选择恰当的应急疏散路径，对于降低矿井人员伤亡和事故等级至关重要。传统的Dijkstra算法不能有效应用于矿井突水的动态环境，只能静态规划出单一的最优逃生路径。为此，提出了1种基于时间当量长度的最优路径分析方法。该方法实现了对传统的Dijkstra算法的动态优化，优化后求解的最优路径随时间、水位高度进行动态变化，并将动态Dijkstra算法与K则最优路径算法相结合，实现对多条最优逃生路径的动态规划。应用表明：优化后的动态D-K算法能够有效适用矿井水害随机性、动态性、复杂性的特点，为受灾人员选择应急逃生路径提供重要的决策支撑。
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关键词:
- 矿井突水 /
- 应急疏散 /
- 最优路径 /
- Dijkstra算法 /
- 动态选择
Abstract:After the occurrence of mine water inrush, choosing the appropriate emergency evacuation path is very important to reduce the casualty and the mine accident level. The traditional Dijkstra algorithm can not be effectively applied to the dynamic environment of mine water inrush. It can only statically plan a single optimal escape path. In view of the limitations of this algorithm, the time equivalent length is introduced to optimize the traditional Dijkstra algorithm to realize the dynamic change of the optimal escape path with time and water level height. Moreover, the optimized Dijkstra algorithm is combined with the K optimal path algorithm to realize the dynamic planning of multiple optimal escape paths. Field application shows that the optimized dynamic D-K algorithm can be effectively applied to mine water inrush with characteristics of randomness, dynamics and complex, which can provide important decision support for affected personnel to choose emergency escape path.
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Keywords:
- mine water inrush /
- emergency evacuation /
- optimal path /
- Dijkstra algorithm /
- dynamic selection
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图 4 不同高度人员在不同水高下的逃生速率
Figure 4. The escape rate of people at different heights in different water levels
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图 5 不同时刻巷道局部矿井突水扩散情况
Figure 5. Water inrush diffusion in local mine at different times
表 1 相关巷道水位上升情况
Table 1 Water level rise in relevant roadway
巷道段 巷道当量长度/
m巷端两端高度差/
m水位上升速率/
（cm·min−1）节点7→节点1 584 5.31 2.93 节点7→节点2 287 1.52 1.71 节点7→节点11 145 0.79 1.75 节点2→节点17 423 2.16 1.64 节点1→节点9 608 5.80 3.07 节点17→节点9 568 5.10 2.89 节点9→节点3 434 3.50 2.60 节点2→节点5 697 2.83 1.31 节点5→节点13 514 3.67 2.30 节点13→节点10 497 3.24 2.10 节点9→节点13 615 3.10 1.62 节点2→节点12 678 2.33 1.11 节点12→节点6 519 3.52 2.18 节点12→节点8 760 3.78 1.60 节点8→节点6 437 4.96 3.66 节点11→节点15 591 1.35 0.74 节点15→节点6 638 2.45 1.24 节点6→节点14 396 1.13 0.92 
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表 2 巷道不同水位下矿工的安全通行系数
Table 2 Safe passage coefficient of miners under different water levels of roadway
水位高度/
m巷道安全
通行系数通行状态 危险程度 0.175 0.9/0.902 8 绿色/绿色 自由通过/自由通过 0.350 0.8/0.805 6 蓝色/绿色 可通过/自由通过 0.525 0.7/0.708 3 黄色/蓝色 需要考虑通过/可通过 0.875 0.5/0.513 9 橙色/黄色 不建议通过/需要考虑通过 1.225 0.3/0.319 4 红色/橙色 不可通过/不建议通过 1.575 0.1/0.125 0 深红色/红色 禁止通过/不可通过
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表 3 相关巷道在t=1/t=15 min时的时间当量长度
Table 3 Time equivalent length of the relevant roadway at t=1/t=15 min
巷道 速度/(m·s−1) 时间当量长度/s t=1 min t=15 min t=1 min t=15 min 节点7→节点1 2 1.68 292.0 347.62 节点7→节点2 2 1.89 143.5 151.85 节点7→节点11 2 1.89 72.5 76.72 节点2→节点17 2 1.88 211.5 225.00 节点1→节点9 2 1.65 304.0 368.48 节点17→节点9 2 1.69 254.0 300.59 节点9→节点3 2 1.74 217.0 249.43 节点2→节点5 2 1.95 348.5 357.44 节点5→节点13 2 1.76 257.0 292.05 节点13→节点10 2 1.82 248.5 273.08 节点9→节点13 2 1.91 307.5 321.99 节点2→节点12 2 2.00 339.0 339.00 节点12→节点6 2 1.80 259.5 288.33 节点12→节点8 2 1.91 380.0 397.91 节点8→节点6 2 1.56 218.5 280.13 节点11→节点15 2 2.00 295.5 295.50 节点15→节点6 2 1.97 319.0 323.86 节点6→节点14 2 2.00 198.0 198.00
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表 4 动态D-K算法在不同时间的最优路径比较
Table 4 Comparison of optimal path search by dynamic D-K algorithm at different times
时间 序号 逃生路线 路径长度/m 通过时间/s t=1 min 1 节点7→节点1→节点9→节点3 1 626 809.00 2 节点7→节点2→节点17→节点9→节点3 1 712 826.00 3 节点7→节点11→节点15→节点6→节点14 1 770 885.00 t=15 min 1 节点7→节点11→节点15→节点6→节点14 1 770 894.08 2 节点7→节点2→节点17→节点9→节点3 1 712 926.87 3 节点7→节点1→节点9→节点3 1 626 965.53
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表 5 传统D-K算法在不同时间的最优路径比较
Table 5 Comparison of optimal path search by traditional D-K algorithm at different times
时间 序号 逃生路径 路径长度 /m 通过时间 /s t=1 min
t=15 min1 节点7→节点1→节点9→节点3 1 626 809.0 2 节点7→节点2→节点5→节点13→节点10 1 995 997.5 3 节点7→节点11→节点15→节点6→节点14 1 770 885.0
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