ANALYSIS AND OPTIMIZATION OF POST-EARTHQUAKE RESTORATION PRIORITY OF BRIDGE NETWORK UPON FRAGMENTATION
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摘要:
为了研究区域性桥梁的抗震优化问题，针对城市桥梁网络的震后修复优先级，引入基于交通密度的网络碎片化分区方法(FaDPa)，提出了考虑恢复性和经济性的双重韧性指标，并针对震后短时抢救以及长时修复的时段特征引入了分阶段优化方法，尤其在长时修复阶段基于不同的修复需求对其进行了分时期处理；在抢险救灾阶段和长时修复阶段分别融入碎片化理论，前者以恢复韧性、时间为目标对抢救顺序进行优化，后者以综合韧性、碎片恢复性、时间对修复顺序进行优化。研究结果表明：基于密度的碎片化理论对桥梁网络不同修复阶段的地震损伤程度做出了不同的划分，此基础上展开的分阶段修复工作在抢险救灾过程中对其综合韧性提升程度达到52.3%，在长期修复过程中不影响韧性优化的前提下增加了碎片恢复性，其功能水平提升可达20.3%；修复优化阶段，经过考虑不同修复方向的双重韧性指标以及分时期处理的优化理论可以根据决策者的需求进行灵活调整，且面临不同修复环境时都具有一定的适应性。
Abstract:In order to study the seismic restoration of regional bridges, aiming at the post-earthquake repair priority of urban bridge networks, a network fragmentation partitioning method (FaDPa) based on traffic density was introduced, and a dual toughness index considering recovery and economy was proposed, and a phased optimization method was introduced according to the time period characteristics of short-term rescue and long-term restoration after earthquake, especially in the long-term restoration stage based on different restoration needs. The fragmentation theory was applied to the rescue and relief stage and the long-term repair stage respectively. The former optimized the rescue order with recovery toughness and time as the target, while the latter optimized the repair order with comprehensive toughness, debris recovery and time. The result shows that the fragmentation theory proposed makes different divisions based on density for the seismic damage degree of different repair stages of the bridge network. The staged repair work on this basis has improved its comprehensive toughness by 52.3% in the process of emergency rescue and disaster relief. Under the premise of not affecting the toughness optimization in the long-term repair process, the fragmentation resilience is increased, and its functional level is increased by 20.3%. In the repair optimization stage, the dual toughness index considering different repair directions and the optimization theory of time-phase processing can be flexibly adjusted according to the needs of decision makers, so that it can adapt to different repair environments, and the repair results considering fragmentation theory supplement the reliability of repair from different dimensions.
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图 1 震后桥梁修复优先级优化流程图
Figure 1. Flow chart of priority optimization for post-earthquake bridge repair
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图 9 震后抢险救灾前碎片化分区
Figure 9. After the earthquake rescue and relief before the fragmentation of the partition
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图 17 碎片化在抢险救灾阶段的系统功能对比
Figure 17. System function comparison of fragmentation in the stage of rescue and relief
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图 18 抢险救灾最优修复次序的碎片相似性
Figure 18. Fragment similarity of the optimal repair order of emergency and disaster relief
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图 19 震后修复阶段优化结果韧性指标对比
Figure 19. Comparison of resilience index of optimization results in post-earthquake restoration stage
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图 20 震后修复阶段优化结果对比
Figure 20. Comparison of optimization results in post-earthquake restoration stage
表 1 节点间距离
Table 1 Distance between node
节点 节点 局部密度 A B C D E F G H I J K L A − 0.89 − 0.89 − 0.10 − 0.95 − − − − 1 B 0.89 − 0.30 − 0.64 − 0.10 − − − − − 2 C − − − − − − − − 2 D − − − − − − − − 2 E − − − − 0.81 0.10 − 0.00 − 2 F 0.10 − 0.81 − 0.59 − − − 0.89 − 0.10 2 G − 0.10 − 0.10 − 0.89 − 0.30 − − − − 3 H 0.95 − 0.59 − 0.81 − 0.30 − − − − − 1 I − − − − 0.10 − − − − 0.10 − 0.59 2 J − − − − − 0.89 − − 0.10 − 0.30 − 2 K − − − − 0.00 − − − − 0.30 − 0.30 3 注：加粗部分表示该节点间距离小于其距离阈值。 
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表 2 桥梁震后能力损伤
Table 2 Capacity damage of bridge after earthquake
损伤等级 通行能力损失率ξ 未破坏(N) 0.00 轻微破坏(L) 0.00 中度破坏(M) 0.25 严重破坏(E) 0.50 基本倒塌(C) 1.00
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表 3 桥梁网络基本参数
Table 3 Basic parameters of bridge network
路段 节点 道路参数 地震参数 桥梁 桥梁参数 路长/km 均交通量(pcu/h) 基本通行能力(pcu/h) 类型 新建费用(百万元) 损伤程度 抢险时间/h 修复
时间/月通行能力损失率ξ 1 (1,2) 0.60 1226 1550 地震断裂带震中位置距路网较近，地震动为浅源地震，震源深度10 km 1 MSSS steel 20.38 E 10 4 0.50 2 (2,3) 0.60 1344 2340 2 MSSS steel 22.75 L − 1 0.00 3 (1,8) 0.60 857 1000 3 MSSS steel 23.45 E 10 3 0.50 4 (1,5) 0.70 984 490 4 MSSS steel 18.50 M − 2 0.25 5 (2,4) 1.00 1923 2340 5 MSSS steel 19.42 C 10 5 1.00 6 (3,4) 0.85 1264 1700 6 MSSS con 25.34 M − 2 0.25 7 (7,8) 0.85 1123 300 7 MSC steel 15.22 N − − 0.00 8 (6,7) 0.80 610 830 8 MSC steel 15.39 E 10 1 0.50 9 (4,5) 0.85 418 470 9 MSC steel 20.54 E 10 4 0.50 10 (8,9) 0.85 556 780 10 MSC steel 21.47 M − 2 0.25 11 (7,10) 0.80 398 500 11 MSC steel 30.05 C 10 5 1.00 12 (6,10) 0.60 536 350 12 MSC con 41.66 E 10 3 0.50 13 (6,11) 0.60 941 1100 13 MSC con 22.56 M − 2 0.25 14 (5,11) 0.60 1231 2340 14 MSC con 30.40 E 10 4 0.50 15 (5,12) 0.70 547 400 15 MSSS con 35.79 E 20 3 0.50 16 (9,10) 0.80 1238 2590 16 MSSS con 20.58 E 10 3 0.50 17 (11,12) 0.85 1024 1550 17 MSSS con 34.22 L − 1 0.00 注：MSSS steel为多跨简支钢梁桥；MSC steel为多跨连续钢梁桥；MSSS con为多跨简支混凝土梁桥；MSC con为多跨连续混凝土梁桥。
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表 4 碎片化分区对比
Table 4 Comparison of fragmented partitions
震前 抢险救灾前 震后修复前 [3, 7] [1] [3, 7, 10] [1, 2, 5, 6, 9] [3, 7] [2, 6] [8] [2, 4, 5, 6, 9, 13, 14, 15, 17] [8] [10] [8, 10, 11, 12, 16] [11] [11] − [12] [12] − [1, 4, 5, 9, 13, 14, 15, 17] [4, 13, 14, 15] − [16] [16] − − 注：加粗部分为每个碎片的密度峰值节点DPN。
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[1] BRUNEAU M, CHANG S E, EGUCHI R T, et al. A Framework to quantitatively assess and enhance the seismic resilience of communities [J]. Earthquake Spectra, 2003, 19(4): 733 − 752. doi: 10.1193/1.1623497
[2] ZOBEL C W, KHANSA L. Characterizing multi-event disaster resilience [J]. Computers & Operations Research, 2014, 42: 83 − 94.
[3] HENRY D, RAMIREZ-MARQUEZ J E. Generic metrics and quantitative approaches for system resilience as a function of time [J]. Reliability Engineering & System Safety, 2012, 99: 114 − 122.
[4] CHEN L C, MILLER-HOOKS E. Resilience: An indicator of recovery capability in intermodal freight transport [J]. Transportation Science, 2012, 46(1): 109 − 123. doi: 10.1287/trsc.1110.0376
[5] BOCCHINI P, FRANGOPOL D M. Optimal resilience- and cost-based postdisaster intervention prioritization for bridges along a highway segment [J]. Journal of Bridge Engineering, 2012, 17(1): 117 − 129. doi: 10.1061/(ASCE)BE.1943-5592.0000201
[6] KARAMLOU A, BOCCHINI P. Sequencing algorithm with multiple-input genetic operators: Application to disaster resilience [J]. Engineering Structures, 2016, 117: 591 − 602. doi: 10.1016/j.engstruct.2016.03.038
[7] EDRISSI A, NOURINEJAD M, ROORDA M J. Transportation network reliability in emergency response [J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 80: 56 − 73. doi: 10.1016/j.tre.2015.05.005
[8] 刘振亮. 考虑震后救援能力的城市桥梁网络抗震性能评估研究[D]. 哈尔滨: 哈尔滨工业大学, 2015. LIU Zhenliang. Seismic performance assessment of Urban bridge network considering the post-disaster evacuation capacity [D]. Harbin: Harbin Institute of Technology, 2015. (in Chinese)
[9] ZHANG W L, WANG N Y, NICHOLSON C. Resilience-based post-disaster recovery strategies for road-bridge networks [J]. Structure and Infrastructure Engineering, 2017, 13(11): 1404 − 1413. doi: 10.1080/15732479.2016.1271813
[10] ANWAR T, LIU C F, VU H L, et al. Partitioning road networks using density peak graphs: Efficiency vs. accuracy [J]. Information Systems, 2017, 64: 22 − 40. doi: 10.1016/j.is.2016.09.006
[11] 侯本伟, 李小军, 韩强, 等. 基于多指标分析的路网单元抗震改造重要度评价[J]. 中国科学: 技术科学, 2018, 48(2): 217 − 228. doi: 10.1360/N092017-00040 HOU Benwei, LI Xiaojun, HAN Qiang, et al. Seismic retrofit priority assessment of highway networks based on multi-indices analysis [J]. Scientia Sinica Technologica, 2018, 48(2): 217 − 228. (in Chinese) doi: 10.1360/N092017-00040
[12] ZOU Q L, CHEN S R. Enhancing resilience of interdependent traffic-electric power system [J]. Reliability Engineering & System Safety, 2019, 191: 106557.
[13] KAVIANI A, THOMPSON R G, RAJABIFARD A, et al. A model for multi-class road network recovery scheduling of regional road networks [J]. Transportation, 2020, 47(1): 109 − 143. doi: 10.1007/s11116-017-9852-5
[14] 吕彪, 高自强, 管心怡, 等. 基于日变交通配流的城市道路网络韧性评估[J]. 西南交通大学学报, 2020, 55(6): 1181 − 1190. doi: 10.3969/j.issn.0258-2724.20191214 LYU Biao, GAO Ziqiang, GUAN Xinyi, et al. Resilience assessment of urban road network based on day-to-day traffic assignment [J]. Journal of Southwest Jiaotong University, 2020, 55(6): 1181 − 1190. (in Chinese) doi: 10.3969/j.issn.0258-2724.20191214
[15] LIU K Z, ZHAI C H, DONG Y. Optimal restoration schedules of transportation network considering resilience [J]. Structure and Infrastructure Engineering, 2021, 17(8): 1141 − 1154. doi: 10.1080/15732479.2020.1801764
[16] 寇峥, 李宁. 基于NSGA-Ⅱ的城市桥梁系统震后可恢复性分析与优化[J]. 工程力学, 2021, 38(3): 148 − 158, 180. doi: 10.6052/j.issn.1000-4750.2020.05.0290 KOU Zheng, LI Ning. Study on earthquake resilience analysis and optimization for urban bridge network system Based on NSGA-II algorithm [J]. Engineering Mechanics, 2021, 38(3): 148 − 158, 180. (in Chinese) doi: 10.6052/j.issn.1000-4750.2020.05.0290
[17] 宗成才, 冀昆, 温瑞智, 等. 城市燃气管网三维度抗震韧性定量评估方法[J]. 工程力学, 2021, 38(2): 146 − 156. doi: 10.6052/j.issn.1000-4750.2020.04.0219 ZONG Chengcai, JI Kun, WEN Ruizhi, et al. Three-dimensional seismic resilience quantification framework for the urban gas network [J]. Engineering Mechanics, 2021, 38(2): 146 − 156. (in Chinese) doi: 10.6052/j.issn.1000-4750.2020.04.0219
[18] 张望欣, 韩强, 温佳年, 等. 基于地震灾害管理的桥梁网络韧性决策框架[J]. 土木工程学报, 2023, 56(4): 72 − 82. doi: 10.15951/j.tmgcxb.21121231 ZHANG Wangxin, HAN Qiang, WEN Jianian, et al. A decision framework for bridge networks resilience based on earthquake disaster management [J]. China Civil Engineering Journal, 2023, 56(4): 72 − 82. (in Chinese) doi: 10.15951/j.tmgcxb.21121231
[19] ZHANG M Y, YANG X J, ZHANG J, et al. Post-earthquake resilience optimization of a rural “road-bridge” transportation network system [J]. Reliability Engineering & System Safety, 2022, 225: 108570.
[20] LIU Z L, LI S C, GUO A X, et al. Comprehensive functional resilience assessment methodology for bridge networks using data-driven fragility models [J]. Soil Dynamics and Earthquake Engineering, 2022, 159: 107326. doi: 10.1016/j.soildyn.2022.107326
[21] SHARMA N, TABANDEH A, GARDONI P. Regional resilience analysis: A multiscale approach to optimize the resilience of interdependent infrastructure [J]. Computer-Aided Civil and Infrastructure Engineering, 2020, 35(12): 1315 − 1330. doi: 10.1111/mice.12606
[22] 缪惠全, 钟紫蓝, 侯本伟, 等. 基于系统动力学的城市供水管网动态抗震韧性评估方法[J]. 工程力学, 2023, 40(12): 99 − 112. doi: 10.6052/j.issn.1000-4750.2022.02.0154 MIAO Huiquan, ZHONG Zilan, HOU Benwei, et al. Dynamic seismic resilience assessment method for water distribution networks based on system dynamics [J]. Engineering Mechanics, 2023, 40(12): 99 − 112. (in Chinese) doi: 10.6052/j.issn.1000-4750.2022.02.0154
[23] WANG D, ZHAO X Y, LIU Y. Effect of spatial variation of earthquake ground motions on seismic vulnerability of urban road network considering building environment [J]. Buildings, 2022, 12(3): 12030308. doi: 10.3390/buildings12030308
[24] 牟健慧, 段培永, 高亮, 等. 基于混合遗传算法求解分布式流水车间逆调度问题[J]. 机械工程学报, 2022, 58(6): 295 − 308. MU Jianhui, DUAN Peiyong, GAO Liang, et al. Hybrid genetic algorithm for distributed flow shop inverse scheduling problem [J]. Journal of Mechanical Engineering, 2022, 58(6): 295 − 308. (in Chinese)
[25] MYEONG S, JUNG Y, LEE E. A study on determinant factors in smart city development: An analytic hierarchy process analysis [J]. Sustainability, 2018, 10(8): 10082606. doi: 10.3390/su10082606
[26] CHANG S E, SHINOZUKA M, MOORE J E. Probabilistic earthquake scenarios: Extending risk analysis methodologies to spatially distributed systems [J]. Earthquake Spectra, 2000, 16(3): 557 − 572. doi: 10.1193/1.1586127
[27] CHANG S E, NOJIMA N. Measuring post-disaster transportation system performance: The 1995 Kobe earthquake in comparative perspective [J]. Transportation Research Part A:Policy and practice, 2001, 35(6): 475 − 494. doi: 10.1016/S0965-8564(00)00003-3
[28] NIELSON B G, DESROCHES R. Analytical seismic fragility curves for typical bridges in the central and southeastern United States [J]. Earthquake Spectra, 2007, 23(3): 615 − 633. doi: 10.1193/1.2756815
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