Article(id=1241793462991917960, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1241793456876618047, articleNumber=null, orderNo=null, doi=10.13197/j.eeed.2025.0401, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1724342400000, receivedDateStr=2024-08-23, revisedDate=1728057600000, revisedDateStr=2024-10-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1773996232983, onlineDateStr=2026-03-20, pubDate=1755792000000, pubDateStr=2025-08-22, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773996232983, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773996232983, creator=13701087609, updateTime=1773996232983, updator=13701087609, issue=Issue{id=1241793456876618047, tenantId=1146029695717560320, journalId=1241701559352995854, year='2025', volume='45', issue='4', pageStart='1', pageEnd='222', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773996231526, creator=13701087609, updateTime=1773997043565, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241796862877958695, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1241793456876618047, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241796862877958696, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1241793456876618047, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=12, ext={EN=ArticleExt(id=1241793463272936344, articleId=1241793462991917960, tenantId=1146029695717560320, journalId=1241701559352995854, language=EN, title=Research on the evaluation method of functional recovery time of urban building clusters considering the influence of multiple factors, columnId=null, journalTitle=Earthquake Engineering and Engineering Dynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In the current context of increasingly constructed urban built environments, the disaster impacts of functional disruptions in urban buildings hit by earthquakes can quickly propagate and intensify through the social chain. To quantify the functional disruption of earthquake-damaged building complexes, this paper focuses on assessing the functional recovery time of urban building complexes after an earthquake and develops a comprehensive assessment framework. The framework employs a fuzzy hierarchical analysis to quantify the impact of key factors, such as building renovation class, regional economy, climate, and topography, on the recovery process. Additionally, the study divides the rehabilitation process of the urban complex into a preparation phase and a repair and reconstruction phase, and develops a systematic assessment model for each phase. In the preparation stage, the assessment model especially considered the impact of the earthquake emergency period and systematically sorted out the time required for five key recovery preparations under different intensities of effects according to the expected intensity of earthquake effects; the assessment model for the repair and reconstruction stage was constructed based on the damaged area of the earthquake-damaged houses as well as the time required for repairing or reconstructing per square meter. The model preliminarily estimates the reconstruction time per unit area of houses of different building structure types in China through in-depth analysis of the quota data, and takes into account the uncertainties in the construction process by using the Monte Carlo simulation method. And the repair time per unit area of a house is derived by reasonably discounting the reconstruction time based on its damage degree. The research results not only provide new perspectives for the theory of urban disaster management, but also provide good data support for the resilience building of the government and enterprises and the rapid development of recovery decisions after disasters.

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在当前城市建筑环境日益复杂的背景下,城市建筑群一旦遭受地震打击而发生功能中断,其灾害影响会迅速通过社会链传播并加剧。为了量化震损建筑群的功能中断,该文聚焦于评估震后城市建筑群的功能恢复时间,并构建了一个综合评估框架。该框架采用模糊层次分析法,量化了建筑装修等级,地区经济、气候和地形地貌等关键因素对恢复进程的影响。此外,研究将城市建筑群的恢复进程划分为准备阶段和维修与重建阶段,并为每个阶段建立了系统的评估模型。在准备阶段,评估模型特别考虑了地震应急期的影响,并根据地震预期作用强度,系统地梳理了不同强度作用下5项关键恢复准备事项所需的时间;维修、重建阶段的评估模型则是基于震损房屋的破坏面积以及每平方米维修或重建所需的时间进行构建的。该模型通过深入分析定额数据,初步估算了我国不同建筑结构类型房屋的单位面积重建时间,并采用蒙特卡洛(Monte Carlo)模拟方法考虑了施工过程中的不确定性,而房屋的单位面积维修时间是基于其破坏程度对重建时间进行合理折减得出的。该研究成果不仅为城市灾害管理理论提供了新的视角,同时也为政府和企业的韧性建设和灾后快速制定恢复决策提供了良好的数据支撑。

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孙柏涛(1961—),男,研究员,博士,主要从事结构抗震和灾害学研究。E-mail:
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王楠(1998—),女,博士研究生,主要从事地震灾害损失评估方法研究。E-mail:

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王楠(1998—),女,博士研究生,主要从事地震灾害损失评估方法研究。E-mail:

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Classification of houses of different decoration levels and values of their influence coefficients

, figureFileSmall=null, figureFileBig=null, tableContent=
装修等级装修物项影响系数(α1
内墙面外墙面天棚楼地面门、窗
一般装修一般涂料一般涂料一般涂料简单的石材塑钢窗、钢木门(窗)1.0
中高档装修高级涂料、贴装饰砖、壁纸及软包等高级涂料贴面砖、幕墙等高级涂料、吊顶、壁纸铺有地板、瓷砖、地毯彩板、铝合金、木门(窗)1.3
), ArticleFig(id=1241802900356272756, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表1, caption=

不同装饰装修等级房屋划分及其影响系数取值

, figureFileSmall=null, figureFileBig=null, tableContent=
装修等级装修物项影响系数(α1
内墙面外墙面天棚楼地面门、窗
一般装修一般涂料一般涂料一般涂料简单的石材塑钢窗、钢木门(窗)1.0
中高档装修高级涂料、贴装饰砖、壁纸及软包等高级涂料贴面砖、幕墙等高级涂料、吊顶、壁纸铺有地板、瓷砖、地毯彩板、铝合金、木门(窗)1.3
), ArticleFig(id=1241802900490490493, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 2, caption=

Statistics on construction time per unit area of different grades of decorative items

, figureFileSmall=null, figureFileBig=null, tableContent=
装修物项装修等级项目综合人工/d均值/d比值比值均值
墙面一般抹灰灰浆0.490.491.591.34
中高级贴砖大理石0.890.78
花岗岩0.89
陶瓷0.68
瓷砖0.64
天棚一般刨花板0.080.131.16
玻璃纤维板0.20
塑料板0.12
中高级装饰板0.100.15
花式0.12
饰面胶合板0.16
石膏板0.19
吊顶0.20
楼地面一般天然石材地面大理石0.320.301.33
花岗岩0.26
中高级人造地面陶瓷0.350.40
地板0.44
地毯0.42
门窗工程一般塑钢门窗0.650.651.29
中高级铝合金门窗0.830.84
装饰门窗0.68
电动门窗1.00
), ArticleFig(id=1241802900700205711, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表2, caption=

不同等级装饰装修物项单位面积施工耗时统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
装修物项装修等级项目综合人工/d均值/d比值比值均值
墙面一般抹灰灰浆0.490.491.591.34
中高级贴砖大理石0.890.78
花岗岩0.89
陶瓷0.68
瓷砖0.64
天棚一般刨花板0.080.131.16
玻璃纤维板0.20
塑料板0.12
中高级装饰板0.100.15
花式0.12
饰面胶合板0.16
石膏板0.19
吊顶0.20
楼地面一般天然石材地面大理石0.320.301.33
花岗岩0.26
中高级人造地面陶瓷0.350.40
地板0.44
地毯0.42
门窗工程一般塑钢门窗0.650.651.29
中高级铝合金门窗0.830.84
装饰门窗0.68
电动门窗1.00
), ArticleFig(id=1241802900834423450, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 3, caption=

Adjustment coefficients considering the influence of regional economic development status

, figureFileSmall=null, figureFileBig=null, tableContent=
人均GDP水平/元(0,100000](100000,150000](150000,+∞)
经济发展水平一般较发达发达
影响系数(α21.00.90.8
), ArticleFig(id=1241802900951863976, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表3, caption=

考虑地区经济发展状况影响的调整系数参考取值

, figureFileSmall=null, figureFileBig=null, tableContent=
人均GDP水平/元(0,100000](100000,150000](150000,+∞)
经济发展水平一般较发达发达
影响系数(α21.00.90.8
), ArticleFig(id=1241802901128024762, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 4, caption=

Reference values of adjustment factors considering the influence of regional climatic conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
地区分类不同气候分区平均气温及其持续日数有效工日/d比值影响系数(α3
Ⅰ类地区年日平均气温大于25 ℃的日数大于等于40 d,且小于5 ℃的日数小于30 d3311.371.4
Ⅱ类地区年日平均气温大于25 ℃的日数小于80 d,且小于 5 ℃的日数大于60 d同时小于90 d2821.171.2
Ⅲ类地区年日平均大于25 ℃的日数小于30 d,气温小于5 ℃的日数大于120 d2421.01.0
), ArticleFig(id=1241802901228688069, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表4, caption=

考虑地区气候条件状况影响的调整系数参考取值

, figureFileSmall=null, figureFileBig=null, tableContent=
地区分类不同气候分区平均气温及其持续日数有效工日/d比值影响系数(α3
Ⅰ类地区年日平均气温大于25 ℃的日数大于等于40 d,且小于5 ℃的日数小于30 d3311.371.4
Ⅱ类地区年日平均气温大于25 ℃的日数小于80 d,且小于 5 ℃的日数大于60 d同时小于90 d2821.171.2
Ⅲ类地区年日平均大于25 ℃的日数小于30 d,气温小于5 ℃的日数大于120 d2421.01.0
), ArticleFig(id=1241802901367100113, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 5, caption=

Reference values of adjustment factor of considering the influence of topography and geomorphic conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
地区分类绝对高度/m影响系数(α4
平原、丘陵地区(0,1500]1.0
山岭、重丘地区(1500,3000]1.2
高原地区(3000,+∞)1.3
), ArticleFig(id=1241802901488734946, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表5, caption=

考虑地区地形地貌状况影响的调整系数参考取值

, figureFileSmall=null, figureFileBig=null, tableContent=
地区分类绝对高度/m影响系数(α4
平原、丘陵地区(0,1500]1.0
山岭、重丘地区(1500,3000]1.2
高原地区(3000,+∞)1.3
), ArticleFig(id=1241802901614564075, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 6, caption=

Judgment matrix and weight allocation of influencing factors for the functional recovery of building clusters

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素(αi装饰装修经济气候地形权重(wi
α1装饰装修1579w10.58
α2经济1/5124w20.23
α3气候1/71/212w30.12
α4地形1/91/41/21w40.07
), ArticleFig(id=1241802901815890685, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表6, caption=

建筑群功能恢复影响因素的判断矩阵及权重分配表

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素(αi装饰装修经济气候地形权重(wi
α1装饰装修1579w10.58
α2经济1/5124w20.23
α3气候1/71/212w30.12
α4地形1/91/41/21w40.07
), ArticleFig(id=1241802901966885642, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 7, caption=

Consistency test for regional characteristic influence factors

, figureFileSmall=null, figureFileBig=null, tableContent=
最大特征向量(λmax计算一致性指标(CI)查找一致性指标(RI)一致性比例(CR)
4.030.010.890.01<0.10
), ArticleFig(id=1241802902088520469, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表7, caption=

区域特性影响因素一致性检验

, figureFileSmall=null, figureFileBig=null, tableContent=
最大特征向量(λmax计算一致性指标(CI)查找一致性指标(RI)一致性比例(CR)
4.030.010.890.01<0.10
), ArticleFig(id=1241802903581692711, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 8, caption=

Statistical table of maintenance preparation items and their required time

, figureFileSmall=null, figureFileBig=null, tableContent=
维修准备事项预期地震作用其他条件区间中位值/d
房屋安全鉴定[29]<M71~3 d2.0
M71~2周10.5
过渡安置规划制定[30]<M71~2周10.5
M73~4周24.5
恢复重建规划编制[31]<M78周28.0
M746周161.0
恢复重建资金筹措国家财政支持[30]20 d10.0
保险1~2周10.5
私人贷款3~4周24.5
施工许可获取[32]1~2周10.5
), ArticleFig(id=1241802903728493364, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表8, caption=

维修准备事项及其所需时间统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
维修准备事项预期地震作用其他条件区间中位值/d
房屋安全鉴定[29]<M71~3 d2.0
M71~2周10.5
过渡安置规划制定[30]<M71~2周10.5
M73~4周24.5
恢复重建规划编制[31]<M78周28.0
M746周161.0
恢复重建资金筹措国家财政支持[30]20 d10.0
保险1~2周10.5
私人贷款3~4周24.5
施工许可获取[32]1~2周10.5
), ArticleFig(id=1241802903858516798, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 9, caption=

Simulation results of reconstruction rate of masonry structure houses

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~30.02250.01940.1255
4~70.0137
非住宅房屋办公1~30.02690.2315
商业
教育4~60.0194
医院
), ArticleFig(id=1241802903975957323, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表9, caption=

砌体结构房屋重建率模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~30.02250.01940.1255
4~70.0137
非住宅房屋办公1~30.02690.2315
商业
教育4~60.0194
医院
), ArticleFig(id=1241802904101786458, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 10, caption=

Simulation results of reconstruction rate of houses with cast-in-place shear wall/frame-shear wall structure

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01130.00900.0095
9~200.0067
非住宅房屋旅馆、酒店1~80.01420.0100
广播电影、电视
办公9~200.0087
商业
教育21~400.0070
医院
), ArticleFig(id=1241802904223421280, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表10, caption=

现浇剪力墙/框架-剪力墙结构房屋重建率模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01130.00900.0095
9~200.0067
非住宅房屋旅馆、酒店1~80.01420.0100
广播电影、电视
办公9~200.0087
商业
教育21~400.0070
医院
), ArticleFig(id=1241802904353444718, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 11, caption=

Simulation results of reconstruction rate of houses with cast-in-place frame structure

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01380.01080.0117
9~200.0078
非住宅房屋旅馆、酒店1~80.01810.0126
广播电影、电视
办公9~200.0103
商业
教育21~300.0093
医院
), ArticleFig(id=1241802904475079546, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表11, caption=

现浇框架结构房屋重建率模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01380.01080.0117
9~200.0078
非住宅房屋旅馆、酒店1~80.01810.0126
广播电影、电视
办公9~200.0103
商业
教育21~300.0093
医院
), ArticleFig(id=1241802904605102980, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 12, caption=

Simulation results of reconstruction rate of assembled concrete structure houses

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01080.00870.0092
9~200.0066
非住宅房屋旅馆、酒店1~80.01300.0097
广播电影、电视
办公9~200.0080
商业
教育21~300.0080
医院
), ArticleFig(id=1241802904739320727, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表12, caption=

装配式混凝土结构房屋重建率模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能层数重建率均值结构均值
住宅房屋1~80.01080.00870.0092
9~200.0066
非住宅房屋旅馆、酒店1~80.01300.0097
广播电影、电视
办公9~200.0080
商业
教育21~300.0080
医院
), ArticleFig(id=1241802904869344164, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 13, caption=

Simulation results of reconstruction rate of steel-framed houses

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能重建率结构均值
非住宅房屋体育场0.00280.0033
交通枢纽楼0.0015
博物馆0.0057
影剧院
购物中心
), ArticleFig(id=1241802904974201773, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表13, caption=

钢结构房屋重建率模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
使用功能重建率结构均值
非住宅房屋体育场0.00280.0033
交通枢纽楼0.0015
博物馆0.0057
影剧院
购物中心
), ArticleFig(id=1241802905108419518, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=EN, label=Table 14, caption=

Adjustment coefficient table of repair rate to reconstruction rate for repairable building clusters at different damage states

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破坏等级折减系数β
基本完好0
轻微破坏9.35
中等破坏偏轻17.85
中等破坏26.35
中等破坏偏重34.85
), ArticleFig(id=1241802905288774606, tenantId=1146029695717560320, journalId=1241701559352995854, articleId=1241793462991917960, language=CN, label=表14, caption=

可修复建筑群各破坏等级维修率与重建率的折减系数(β)对照表

, figureFileSmall=null, figureFileBig=null, tableContent=
破坏等级折减系数β
基本完好0
轻微破坏9.35
中等破坏偏轻17.85
中等破坏26.35
中等破坏偏重34.85
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考虑多因素影响的城市建筑群功能恢复时间评估方法研究
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王楠 1, 2 , 孙柏涛 1, 2, 3 , 张桂欣 1, 2
地震工程与工程振动 | 2025,45(4): 1-12
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地震工程与工程振动 | 2025, 45(4): 1-12
考虑多因素影响的城市建筑群功能恢复时间评估方法研究
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王楠1, 2 , 孙柏涛1, 2, 3 , 张桂欣1, 2
作者信息
  • 1.中国地震局工程力学研究所 地震工程与工程振动重点实验室,黑龙江 哈尔滨 150080
  • 2.地震灾害防治应急管理部重点实验室,黑龙江 哈尔滨 150080
  • 3.地震和地质灾害生命搜索救援技术应急管理部重点实验室,北京 100049
  • 王楠(1998—),女,博士研究生,主要从事地震灾害损失评估方法研究。E-mail:

通讯作者:

孙柏涛(1961—),男,研究员,博士,主要从事结构抗震和灾害学研究。E-mail:
Research on the evaluation method of functional recovery time of urban building clusters considering the influence of multiple factors
Nan WANG1, 2 , Baitao SUN1, 2, 3 , Guixin ZHANG1, 2
Affiliations
  • 1.Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China
  • 2.Key Laboratory of Earthquake Disaster Mitigation, Ministry of Emergency Management, Harbin 150080, China
  • 3.Key Laboratory of Life Search and Rescue Technology for Earthquake and Geological Disaster, Ministry of Emergency Management, Beijing 100049, China
出版时间: 2025-08-22 doi: 10.13197/j.eeed.2025.0401
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在当前城市建筑环境日益复杂的背景下,城市建筑群一旦遭受地震打击而发生功能中断,其灾害影响会迅速通过社会链传播并加剧。为了量化震损建筑群的功能中断,该文聚焦于评估震后城市建筑群的功能恢复时间,并构建了一个综合评估框架。该框架采用模糊层次分析法,量化了建筑装修等级,地区经济、气候和地形地貌等关键因素对恢复进程的影响。此外,研究将城市建筑群的恢复进程划分为准备阶段和维修与重建阶段,并为每个阶段建立了系统的评估模型。在准备阶段,评估模型特别考虑了地震应急期的影响,并根据地震预期作用强度,系统地梳理了不同强度作用下5项关键恢复准备事项所需的时间;维修、重建阶段的评估模型则是基于震损房屋的破坏面积以及每平方米维修或重建所需的时间进行构建的。该模型通过深入分析定额数据,初步估算了我国不同建筑结构类型房屋的单位面积重建时间,并采用蒙特卡洛(Monte Carlo)模拟方法考虑了施工过程中的不确定性,而房屋的单位面积维修时间是基于其破坏程度对重建时间进行合理折减得出的。该研究成果不仅为城市灾害管理理论提供了新的视角,同时也为政府和企业的韧性建设和灾后快速制定恢复决策提供了良好的数据支撑。

城市韧性  /  地震灾害风险评估  /  城市建筑功能中断  /  功能恢复时间评估  /  Monte Carlo模拟

In the current context of increasingly constructed urban built environments, the disaster impacts of functional disruptions in urban buildings hit by earthquakes can quickly propagate and intensify through the social chain. To quantify the functional disruption of earthquake-damaged building complexes, this paper focuses on assessing the functional recovery time of urban building complexes after an earthquake and develops a comprehensive assessment framework. The framework employs a fuzzy hierarchical analysis to quantify the impact of key factors, such as building renovation class, regional economy, climate, and topography, on the recovery process. Additionally, the study divides the rehabilitation process of the urban complex into a preparation phase and a repair and reconstruction phase, and develops a systematic assessment model for each phase. In the preparation stage, the assessment model especially considered the impact of the earthquake emergency period and systematically sorted out the time required for five key recovery preparations under different intensities of effects according to the expected intensity of earthquake effects; the assessment model for the repair and reconstruction stage was constructed based on the damaged area of the earthquake-damaged houses as well as the time required for repairing or reconstructing per square meter. The model preliminarily estimates the reconstruction time per unit area of houses of different building structure types in China through in-depth analysis of the quota data, and takes into account the uncertainties in the construction process by using the Monte Carlo simulation method. And the repair time per unit area of a house is derived by reasonably discounting the reconstruction time based on its damage degree. The research results not only provide new perspectives for the theory of urban disaster management, but also provide good data support for the resilience building of the government and enterprises and the rapid development of recovery decisions after disasters.

urban resilience  /  earthquake disaster risk assessment  /  urban building function disruption  /  functional recovery time assessment  /  Monte Carlo simulation
王楠, 孙柏涛, 张桂欣. 考虑多因素影响的城市建筑群功能恢复时间评估方法研究. 地震工程与工程振动, 2025 , 45 (4) : 1 -12 . DOI: 10.13197/j.eeed.2025.0401
Nan WANG, Baitao SUN, Guixin ZHANG. Research on the evaluation method of functional recovery time of urban building clusters considering the influence of multiple factors[J]. Earthquake Engineering and Engineering Dynamics, 2025 , 45 (4) : 1 -12 . DOI: 10.13197/j.eeed.2025.0401
随着科技的不断发展和城市基础设施的不断升级,基础设施与建筑间的相互影响日益紧密。在这一背景下,地震事件带来的影响可能会迅速通过供应链、业务网络等社会链条扩散,致使因建筑破坏导致的城市功能中断后果不断加剧[1]。企业、员工等利益相关者在遭受地震灾害打击后,希望通过尽快恢复生产、正常工作来弥补自身的损失。进而,社会的发展对于抗震研究提出了新的要求:如何评估城市乃至整个社会的功能恢复时间,以帮助政府、企业以及民众做出进一步决策[2-3]。特别是在大中城市,开展城市功能中断时间评估已成为提升城市韧性、有效减轻灾害后果的关键一环。
针对地震灾害引发的城市功能中断问题,众多专家、学者已经提出了多样化的研究理念与方法。20世纪80年代末,美国联邦应急管理局(Federal Emergency Management Agency,FEMA)与美国应用技术委员会(Applied Technology Council,ATC)在ATC-13中率先提出了基于功能损失率的建筑中断时间评估框架,该框架将建筑物的功能中断时间视为受损程度、重要性、恢复资源可及性以及设施设备功能水平的综合函数[4]。通过将这些自变量的变化映射为建筑功能损失水平,进而评估出不同功能损失水平下的建筑功能恢复时间。这一研究理念为后续的研究思路打下了重要基础。
进入21世纪,随着全球范围内城市化进程的快速推进,韧性城市逐渐成为国内外防震减灾领域研究和实践的热点[5]。城市建筑的功能恢复时间,作为评估城市韧性水平的关键指标之一,日益受到学术界的广泛关注。中国学者谢礼立院士基于ATC-13[4]报告中给出的不同破坏等级建筑功能恢复时间,认为在实际重建过程中,房屋往往难以立即恢复全部功能。因此,他主张对报告的完全恢复天数进行更为实际的调整,即取原设定天数的2/3作为参考[6]
美国地质调查局(United States Geological Survey,USGS)基于上述成果主导了一项关于海沃德断层发生破坏性地震的情景研究[7]。该情景假设2018年8月旧金山湾区东湾海沃德断层上发生MW7.0主震[8]造成了一栋符合最新规范建造的40层钢框架高层办公楼发生轻微破坏。虽然仅是轻微破坏,但该栋办公楼确需要6~13个月才能恢复使用,远超实际修复所需的4个月[9]。主要原因是地震后的额外准备和停工时间。经过进一步分析,该栋建筑的修复成本仅占重置成本的12.3%(1.710万美元),而停产的损失却十分惊人。假设该栋写字楼中员工数仅为100人,以2018年旧金山市人均GDP 6万美元计算[10],功能中断带来的停产损失将是修复成本的63倍以上。
2022年,中国学者孙柏涛带领其科研团队,将海沃德相关成果引入了中国。完成了对海沃德地震灾害情景研究成果的本土化编译。在细致的文献梳理过程中发现,尽管单体建筑层面的功能恢复研究已相当丰富,但针对区域或城市尺度的建筑群功能恢复时间评估方法仍存在不足[11-12]。为此,他们以砌体结构为切入点,综合考量了建筑的使用功能、重要性等级及层数等因素,构建了一套针对不同恢复目标下的城市建筑维修与重建时间评估框架[13]
为了进一步完善、补全不同结构类型建筑群的功能恢复时间评估基础数据,也为了进一步丰富既有群体建筑韧性评估框架,本研究致力于开发一套完整的、考虑多种影响因素的城市建筑功能恢复时间评估体系。该方法综合了恢复过程的各个阶段,并量化了建筑结构特性(包括结构类型、使用功能、装修等级),以及地区经济、气候和地形地貌等区域特性对恢复进程的影响,从而提高了评估结果的科学性和可靠性。同时,本研究还提供了不同结构类型房屋单位面积的重建时间,以及不同破坏程度下可修复房屋的单位面积维修时间,并通过Monte Carlo模拟方法对其进行了修正。这些数据不仅丰富了基础数据集,也为相关研究人员提供了参考,还为政府制定科学决策和企业的灾后恢复策略制定提供了依据。
城市建筑群的功能恢复进程是一个连贯且复杂的动态过程,受到多重因素的共同影响,并展现出多维度、多阶段的特性。为了科学、合理地量化这一进程及诸多因素的影响,本节首先分析了城市建筑功能中断时间的概念及组成。并构建了相应的数学模型,该模型系统地整合了城市功能中断时间的各个关键组成要素,包括:功能恢复准备时间、修复与重建时间,以及多种因素共同作用对于整个恢复进程的影响程度。
城市建筑群功能恢复时间在概念上是指某一区域的建筑物群在地震及其次生灾害作用下遭受破坏而损失或完全丧失其原有使用功能,通过一系列维修、加固及重建措施,最终恢复至震前某一可用状态所需花费的时间[13-14]。这一过程可分为3个主要阶段:临震应急响应阶段,恢复准备与过渡阶段和全面恢复与重建阶段[15-16]。其中,前2阶段主要以救援和准备恢复工作为主,建筑群的实际功能恢复主要集中在第3阶段。鉴于此,本研究将前2个阶段定义为“区域建筑群功能恢复的准备期”,将第3阶段明确为“建筑群的维修与重建期”,见图1
由1.1节可知,城市建筑群功能恢复时间是由准备期和维修与重建期共同决定的复合函数。实际上,区域建筑群在进行维修和重建工作时,不仅受到建筑自身特性的影响,还受到所处区域特性的影响。为了全面评估这些因素,本节构建了一个综合评估模型,如式(1)所示:
式中:TD为一个城市震损建筑群的功能恢复时间;α为综合考虑多种因素对恢复时间造成的影响系数;Td为建筑群功能恢复的准备时间,具体指在维修和重建工作正式启动之前各项准备工作所投入的时间;Tr为震损建筑群的维修、重建时间。
在区域层面,城市建筑群的功能恢复是一个复杂的多维过程。这一过程不仅受建筑物的结构类型、使用功能和装修程度等建筑物自身特性的影响,还深受灾区经济状况、气候条件和地形地貌等区域特性因素的影响。由于建筑物的结构类型和使用功能直接决定了建筑物建造时间的长短,因此本研究在基础数据收集阶段就对这些关键特性进行了细致区分。
故而,本节集中分析了建筑物的装修等级,以及区域经济、气候和地形地貌等因素对恢复过程的影响。并通过层次分析法量化分析了这些因素的综合效应,以确定它们对建筑群功能恢复时间的影响程度和相对重要性。
房屋功能的中断很大程度上是因为承载其使用性能和舒适性能的装饰装修发生了破坏。同时,这些装修也决定了维修工作的复杂性和时长。孙柏涛等[17]研究,大中城市新旧住宅的装修普及率已超60%。这一趋势表明,现代房屋几乎无不经过装修即投入使用。鉴于此,本研究参照《建筑安装工程工期定额》[18](简称“定额”),对装修标准进行了合理分类,将住宅装修分为一般装修和中高档装修两大类。具体分类标准是:若房屋装修包含表1所示任一类别中的3项或以上特征,则归入相应装修等级。为量化上述装修等级对建筑功能恢复时间的影响,本节基于《全国统一建筑装饰装修工程消耗量定额》总结分析了表1中五类装修项目采用不同材料和复杂程度工序的平均人工消耗(工日)[19]。通过比较中高档与一般装修在单位面积上的平均工时消耗,以消除单位影响,并计算了所有比值的平均数,以此反映不同装修等级房屋功能恢复时间的差异。详细的数据处理和分析结果见表2
城市的灾后恢复速率深受地区经济状况、气候条件以及地形地貌等区域特性因素的影响,这些因素不仅决定了恢复工作的起点和基础条件,还是整个功能恢复时间评估模型的斜率。鉴于此,本节分别对上述3个核心影响因素进行了讨论,规定了等级划分标准以及影响系数。
经济状况是决定受灾区域灾后恢复速度的重要因素之一,因为其直接关系到可用资源的多寡和修复能力的大小。为了客观衡量受灾区域的经济发展水平,本研究采用人均GDP作为关键指标,并依据中国国家统计局2024年发布的统计数据[20],将受灾区域的经济状况划分为3个经济发展梯度。基于经济发展水平与恢复速度正相关的逻辑,通过专家经验法为每个经济梯度指定了相应的恢复速度影响系数,具体数值见表3
气候条件对房屋维修和重建的设计及施工有着重要影响,特别是在保温、隔热和防雨性能方面[1521]。以中国为例,不同地区的气候特点导致了砌体房屋外墙厚度的差异:东北地区的寒冷气候通常需要37~49 cm的厚墙以保持温暖;中部地区由于气候温和,外墙厚度一般在24~37 cm之间;而南方的湿热气候则倾向于使用18~24 cm墙体或空斗墙体[22]。综上所述,气候特征不仅决定了施工的工作量,也直接影响了施工效率和施工期。
为了量化上述影响,本研究根据GB 50178—1993《建筑气候区划标准》[23]和相关研究成果[24],对适宜进行室外施工的气候条件进行了假设:当日平均气温高于5 ℃时,施工活动可以顺利进行;日平均气温低于5 ℃时,施工活动则无法进行;当日平均气温超过25 ℃时,施工效率可能会下降10%。基于这些假设,本研究进一步将中国划分为3个气候分区,以量化气候因素对维修时间的具体影响:
1)Ⅰ类地区:年平均气温较高,全年温暖湿润,一年中有超过331 d适合施工。
2)Ⅱ类地区:冬季寒冷干燥,夏季温暖多雨,一年中有超过282 d适合施工。
3)Ⅲ类地区:冬季漫长寒冷,一年中有超过242 d适合施工。
三类地区的划分标准及有效工日的计算方法见表4。为了将气候对施工的影响具体量化,本研究将Ⅲ类地区定义为施工条件最不利情况,并以此作为参照点。通过比较其他地区的有效工日与Ⅲ类地区,计算得出各地区的影响系数。
地形地貌是影响工程设计、施工、养护及管理难度的重要因素之一[25]。例如,在高海拔地区,不仅气温低、氧气稀薄,而且地势崎岖。这给运输工作带来了极大的挑战。此外,工人在这样的环境下施工,体力消耗加快,工作效率降低。因此,本研究参考《公路工程预算定额》中:对于施工区域海拔超过3.0 km的情况,由于工作条件极为严苛,建议将施工成本上调1.3倍[26]。对于海拔在1.5~3.0 km之间的区域,通过计算1.0~1.3之间的中间值作为调整系数,为使系数均保留一位小数最终取1.2,以此量化地形地貌对建筑群功能恢复时间的影响。具体的调整系数和其对恢复时间的影响见表5
城市建筑群的功能恢复是一个复杂的过程,受到多种因素的影响。为了全面评估这些因素的综合效应,本节运用层次分析法对这些影响因素进行权重分配。依据模糊层次分析中的标度方法[27],构建了判断矩阵,见表6。判断矩阵中涵盖了四类主要影响因素以及相对重要性。进一步地,本节计算了整个判断矩阵的一致性比例来确认其是否通过了一致性检验,从而确保评估的合理性。详细的计算过程和结果见表7。由于判断矩阵的一致性比例低于0.10,表明其具有良好的一致性,确保了权重分配的合理性和科学性。
在分析了上述各种影响因素的权重之后,本研究构建了一个计算模型来确定综合影响系数α,该系数反映了上述因素对建筑功能恢复时间的综合影响。计算模型如式(2)所示:
式中:α为考虑了不同因素对建筑群功能恢复时间影响的综合系数;αi为各个独立的影响因素,当i取不同值时代表不同的影响因素;wi为每个影响因素对应的权重系数,用于衡量每个因素对城市建筑群功能恢复影响的相对重要性,具体取值见表6
震损建筑群正式启动维修和重建工作之前,通常会经历一个关键的准备阶段,这个阶段包括了地震应急期和一系列耗时的准备工作。为了评估这部分准备时间,本节根据其内涵建立了相应的评估模型,并根据真实震例,梳理、总结了不同地震作用强度下5项较为关键的准备工作及耗时。
区域建筑功能恢复的准备时间通常分为2个主要阶段:地震应急期和恢复准备期,具体的评估模型为
式中:Td为某一评估区域所需的总恢复准备时间;Tpj为在重建工作开始前各项准备工作所需的时间,j取不同的值代表不同的准备事项;Te为地震应急期,这一时期主要以应急救援活动为主,地震强度小于7级时,Te通常取10 d;当地震强度达到或超过7级时,Te则延长至20 d[16]。其中,对于关键准备工作所花费的时间梳理和总结见3.2节。
在正式开展维修和重建工作之前,一些关键性的准备工作是不可或缺的,且往往需要大量时间投入。因此,本节借鉴海沃德地震情景中的准备经验梳理了以下5个核心准备环节:
1)震后房屋安全鉴定:对建筑物的受损情况进行鉴定并评估其安全性。
2)过渡安置规划制定:包括临时住所建设选址、提供基本生活设施以及进行心理安抚等,这些准备工作涉及多方面的协调与资源调配。
3)恢复重建规划编制:基于震损评估结果制定详细的恢复重建规划,包括:城市重新规划、维修方案设计、编制施工计划等。
4)恢复重建资金筹措:通过申请政府补助、动员社会捐赠、推进保险理赔等多种渠道筹集所需资金。
5)施工许可准许:提交所需材料,申请并等待相关部门的审查与批准。
在进行上述准备工作时,本研究参考了奥雅纳公司开发的基于韧性的下一代建筑物抗震设计倡议(REDi Rating System),并借鉴了其中提供的美国应急响应计划的准备时间经验[28]。据此,梳理并总结了在不同预期地震作用强度下,这些准备工作在中国所需的时间范围见表8
城市建筑群功能恢复时间的核心组成部分是震损建筑群的维修、重建时间,这一时间的长短取决于受损房屋的破坏面积和破坏程度。由于并非所有受损建筑都适宜进行维修,对于那些遭受严重破坏或毁坏的建筑,无论是从技术难度还是从经济角度考虑,进行维修都是不切实际的,因此本研究将这些建筑归类为重建建筑群[29]。而将那些发生轻微破坏和(或)中等破坏具有维修价值的建筑视为可修建筑群。基于此,本研究在评估某一区域建筑功能恢复时间时采取了一种综合方法:首先,分别计算评估区内不同结构类型震损建筑群的维修和重建时间;然后,选取其中的最大值作为该区域建筑群维修、重建时间。具体的计算表达式为
式中:Tr为整个区域震损建筑维修、重建总时间;A破坏面积为某种结构类型和破坏等级下房屋的破坏面积;而T维修率/重建率为某种结构类型和破坏等级下房屋单位面积的维修或者重建时间。
房屋重建率是指发生“严重破坏”和“毁坏”的不同结构类型房屋在重建过程中每平方米所需的时间。获取这一时间的方法主要有2种:首先,可以通过统计分析得到,但这种方法得到的数据可能存在较大的离散性;其次,可以通过分析民用建筑工程的工期定额数据来确定不同结构类型房屋的单体建造时间。然后基于这些数据,进一步计算出房屋的重建率。本研究采取了第2种方法,并考虑到施工过程中可能存在的不确定性因素,如施工队伍的技术水平、施工方法和劳动力素质等。通过Monte Carlo模拟方法,对我国常见的砌体结构、现浇剪力墙结构、框架结构和装配式混凝土结构等房屋类型进行了模拟,以进一步修正它们的重建率。模拟结果见图2
在模拟过程中,本研究选取了出现频次最高、最具代表性的数值,作为特定结构类型房屋重建率的最佳值,具体的计算结果见表9~表12。对于钢结构房屋,由于其多用于特定建筑如体育馆、剧院等,存量相对较小,数据较少,因此难以进行全面的Monte Carlo模拟。针对这种情况,本节采用了直接计算法,即通过单体建筑建造时间与建筑面积的比值来为钢结构房屋的重建率提供一个建议性值,见表13
房屋维修率是指发生轻微破坏和中等破坏不同结构类型房屋在维修过程中每平方米所需的时间。鉴于通过传统统计方法获取此类数据存在困难,本研究基于实际震例调研和专家咨询的方法,根据房屋的破坏等级对重建率进行合理折减,从而得到维修率,具体的维修率相对于重建率的折减系数见表14
由于在汶川地震期间,WANG等[13]在进行地震现场房屋安全鉴定时观察到:被判定为中等破坏的房屋在破坏程度上存在明显差异。他们尝试将汶川地震中发生中等破坏的房屋细分为中等破坏偏轻、中等破坏和中等破坏偏重3个子类别,以帮助政府做出下一步举措。这一尝试不仅在汶川地震中取了一定的成功,积累了一定的经验,并在后续的地震现场工作中反复验证了这一举措的科学性和合理性。因此,本研究基于这一经验,进一步将地震现场损失评估规范中的中等破坏等级(损失比区间为16%~45%)细分中等破坏偏轻、中等破坏和中等破坏偏重3个子类别。并将上述损失比区间进行三等分以得到3个子类别的破坏程度。并据此,给出了中等破坏等级的维修率相对于重建率的折减系数。值得注意的是,在不容易进一步判断中等破坏房屋属于哪一破坏等级时,可直接统一按照中等破坏进行考虑。
随着现代化进程的不断推进,建筑环境日益复杂。城市及其周边的建筑群一旦发生破坏,由其引发的功能中断后果将通过产业链、生活链不断传播、加剧。由此引发的功能中断损失将不可估量。鉴于此,本研究聚焦于地震后城市建筑群功能恢复时间的评估,旨在为政府和企业震前制定、实施备灾计划,震后指导恢复重建工作提供依据。具体地,本研究完成了以下四个方面的工作:
1)完善了城市建筑群功能恢复时间评估框架。详细阐述了城市建筑群功能恢复时间的内涵,深入分析了其组成以及工作逻辑。认识到震后的不同阶段的恢复需求不同,将整个恢复进程划分为准备阶段、维修与重建阶段。并据此梳理了评估功能恢复时间的流程与框架,建立了考虑地震应急期和准备时间的完整的功能恢复时间评估模型。
2)补充、完善了城市建筑群维修与重建时间评估模型。针对当前建筑群功能恢复时间评估体系中存在的数据不足与模型局限,本研究采用了基于定额数据的方法并结合Monte Carlo模拟技术,为不同使用功能和层数的房屋类型(包括砌体结构、现浇剪力墙结构、框架-剪力墙结构、现浇框架结构以及装配式钢筋混凝土结构)提供了重建率的估算。此外,还通过专家经验法确定了的不同破坏等级下房屋维修率。
3)综合考虑并量化了多种恢复影响因素。综合考虑了两类关键因素:房屋装修等级以及受灾区域特性(包括经济状况、气候条件和地形地貌)对建筑群功能恢复时间的影响。并分别对上述因素的影响程度进行了细致的分级和量化。然后,通过层次分析法对上述各影响因素进行了分配权重与组合考虑,综合量化了这些因素对恢复进程的影响程度。
4)总结了5项关键准备事项花费时间。针对恢复初期至关重要的准备阶段,系统地总结、梳理了5项关键且耗时的准备事项:震后房屋安全鉴定、过渡安置规划制定、恢复重建规划编制、恢复重建资金筹措和施工许可获取。考虑到不同水平地震作用强度决定了准备工作开展的困难程度,对各项准备工作在不同地震作用下所需的时间进行了合理估算与赋值。
  • 国家重点研发计划项目(2022YFC3003600)
  • 黑龙江省重点研发计划项目(GA22C001)
  • 中国地震局地震工程与工程振动重点实验室重点专项(2021EEEVL0203)
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2025年第45卷第4期
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doi: 10.13197/j.eeed.2025.0401
  • 接收时间:2024-08-23
  • 首发时间:2026-03-20
  • 出版时间:2025-08-22
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  • 收稿日期:2024-08-23
  • 修回日期:2024-10-05
基金
国家重点研发计划项目(2022YFC3003600)
黑龙江省重点研发计划项目(GA22C001)
中国地震局地震工程与工程振动重点实验室重点专项(2021EEEVL0203)
作者信息
    1.中国地震局工程力学研究所 地震工程与工程振动重点实验室,黑龙江 哈尔滨 150080
    2.地震灾害防治应急管理部重点实验室,黑龙江 哈尔滨 150080
    3.地震和地质灾害生命搜索救援技术应急管理部重点实验室,北京 100049

通讯作者:

孙柏涛(1961—),男,研究员,博士,主要从事结构抗震和灾害学研究。E-mail:
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https://castjournals.cast.org.cn/joweb/dzgcygczd/CN/10.13197/j.eeed.2025.0401
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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