Article(id=1228295919511204408, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228295917908980268, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.2025.03.015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1677513600000, receivedDateStr=2023-02-28, revisedDate=1682524800000, revisedDateStr=2023-04-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1770778167846, onlineDateStr=2026-02-11, pubDate=1741536000000, pubDateStr=2025-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770778167846, onlineIssueDateStr=2026-02-11, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770778167846, creator=13701087609, updateTime=1770778167846, updator=13701087609, issue=Issue{id=1228295917908980268, tenantId=1146029695717560320, journalId=1225147924628267009, year='2025', volume='38', issue='3', pageStart='449', pageEnd='662', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770778167464, creator=13701087609, updateTime=1770949125482, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1229012967862235389, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228295917908980268, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1229012967862235390, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228295917908980268, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=587, endPage=594, ext={EN=ArticleExt(id=1228295919758668345, articleId=1228295919511204408, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Discussion on the optimum number of input ground motions in seismic fragility analysis of underground structures by cloud method, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Based on the seismic fragility method,this paper designed a random sampling procedure to investigate the effect of different amounts of input ground motions on the seismic fragility curves of underground structures in the cloud method. Taking a shallow-buried subway station with two-story and three-span as the research object,a non-linear dynamic interaction finite element model of the soil-underground structure was established,and 350 natural ground motions were selected as inputs to calculate the seismic response. The seismic fragility curves were constructed based on PGA-IDR finally. The results show that the amount of input ground motions has a greater effect on the PGA thresholds for each performance level of underground structures when the amount is less than 190. When the amount is greater than 190,the seismic fragility curves for minor and moderate damage to underground structures are not affected by the amount;when the amount is greater than 280,the curves for extensive damage and collapse are negligibly affected by the amount. When the underground structure is in an area with a low probability of strong seismic threat,this paper recommends 190 natural ground motions as inputs,otherwise,it should be 280.

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本文基于地震易损性分析方法,设计样本随机抽取程序,探究了云图法中不同输入地震动数量对于地下结构地震易损性曲线的影响。以浅埋两层三跨地铁车站结构为研究对象,建立土-地下结构非线性动力相互作用有限元模型,选取350条天然地震动记录作为输入,计算获得了350个工况下该地下结构的地震响应。选取层间位移角(IDR)作为结构地震损伤参数,地震动峰值地表加速度(PGA)作为地震动强度参数,构建了该地下结构的地震易损性曲线。结果表明,当输入地震动数量小于190条时,输入数量对地下结构各抗震性能等级的PGA阈值影响较大;当输入地震动数量大于190条时,地下结构的轻微破坏及中度破坏的地震易损性曲线不受输入数量的影响;当输入地震动数量大于280条时,严重破坏及倒塌的曲线受输入数量的影响也基本可忽略。当常见的两层三跨地下结构处于强震(PGA < 0.3g)威胁概率较低的区域时,本文推荐选用190条天然地震动作为输入,当处于强震威胁概率较高的区域时,推荐输入280条天然地震动。

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庄海洋(1978—),男,博士,教授。E-mail:
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IDR quantification system of seismic performance levels for subway station structure with two-story and three-span and PGA thresholds

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抗震性能等级IDR限值IDR中值/%μ/g
基本完好IDR≤0.126%
轻微破坏0.126%<IDR≤0.266%0.1960.355
中度破坏0.266%<IDR≤0.450%0.3580.447
严重破坏0.450%<IDR≤0.813%0.6320.556
倒塌IDR>0.813%1.2000.711
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两层三跨地铁车站结构抗震性能等级IDR量化体系及PGA阈值

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抗震性能等级IDR限值IDR中值/%μ/g
基本完好IDR≤0.126%
轻微破坏0.126%<IDR≤0.266%0.1960.355
中度破坏0.266%<IDR≤0.450%0.3580.447
严重破坏0.450%<IDR≤0.813%0.6320.556
倒塌IDR>0.813%1.2000.711
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The results of the sample groups and their error rate compared with the control group

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编号轻微破坏中度破坏严重破坏倒塌
μ/g误差率/%μ/g误差率/%μ/g误差率/%μ/g误差率/%
190#0.3591.080.4592.710.5804.280.7546.08
200#0.3601.570.4623.430.5855.210.7627.26
210#0.3570.740.4582.390.5783.960.7525.76
220#0.3591.310.4592.750.5794.140.7515.72
230#0.3601.600.4603.010.5804.350.7535.89
240#0.3591.120.4582.390.5763.590.7464.97
250#0.3570.600.4561.960.5743.270.7444.75
260#0.3520.790.4381.920.5392.970.6814.14
270#0.3501.280.4382.080.5402.820.6853.66
280#0.3550.090.4521.160.5682.190.7343.35
290#0.3550.010.4440.730.5481.430.6952.20
300#0.3550.050.4480.350.5600.720.7191.15
350#0.3550.4470.5560.711
), ArticleFig(id=1228312958837649922, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228295919511204408, language=CN, label=表2, caption=

样本组的结果及其与对照组的误差率

, figureFileSmall=null, figureFileBig=null, tableContent=
编号轻微破坏中度破坏严重破坏倒塌
μ/g误差率/%μ/g误差率/%μ/g误差率/%μ/g误差率/%
190#0.3591.080.4592.710.5804.280.7546.08
200#0.3601.570.4623.430.5855.210.7627.26
210#0.3570.740.4582.390.5783.960.7525.76
220#0.3591.310.4592.750.5794.140.7515.72
230#0.3601.600.4603.010.5804.350.7535.89
240#0.3591.120.4582.390.5763.590.7464.97
250#0.3570.600.4561.960.5743.270.7444.75
260#0.3520.790.4381.920.5392.970.6814.14
270#0.3501.280.4382.080.5402.820.6853.66
280#0.3550.090.4521.160.5682.190.7343.35
290#0.3550.010.4440.730.5481.430.6952.20
300#0.3550.050.4480.350.5600.720.7191.15
350#0.3550.4470.5560.711
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关于地下结构云图法地震易损性分析中输入地震动最优数量的探讨
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庄海洋 1, 2 , 杨靖 2 , 刘园园 2 , 唐柏赞 1
振动工程学报 | 2025,38(3): 587-594
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振动工程学报 | 2025, 38(3): 587-594
关于地下结构云图法地震易损性分析中输入地震动最优数量的探讨
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庄海洋1, 2 , 杨靖2, 刘园园2, 唐柏赞1
作者信息
  • 1.华东交通大学土木建筑学院,江西 南昌 330013
  • 2.南京工业大学岩土工程研究所,江苏 南京 210009

通讯作者:

庄海洋(1978—),男,博士,教授。E-mail:
Discussion on the optimum number of input ground motions in seismic fragility analysis of underground structures by cloud method
Haiyang ZHUANG1, 2 , Jing YANG2, Yuanyuan LIU2, Baizan TANG1
Affiliations
  • 1.School of Civil Engineering and Architechue,East China Jiaotong University,Nanchang 330013,China
  • 2.Institute of Geotechnical Engineering,Nanjing Tech University,Nanjing 210009,China
出版时间: 2025-03-10 doi: 10.16385/j.cnki.issn.1004-4523.2025.03.015
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本文基于地震易损性分析方法,设计样本随机抽取程序,探究了云图法中不同输入地震动数量对于地下结构地震易损性曲线的影响。以浅埋两层三跨地铁车站结构为研究对象,建立土-地下结构非线性动力相互作用有限元模型,选取350条天然地震动记录作为输入,计算获得了350个工况下该地下结构的地震响应。选取层间位移角(IDR)作为结构地震损伤参数,地震动峰值地表加速度(PGA)作为地震动强度参数,构建了该地下结构的地震易损性曲线。结果表明,当输入地震动数量小于190条时,输入数量对地下结构各抗震性能等级的PGA阈值影响较大;当输入地震动数量大于190条时,地下结构的轻微破坏及中度破坏的地震易损性曲线不受输入数量的影响;当输入地震动数量大于280条时,严重破坏及倒塌的曲线受输入数量的影响也基本可忽略。当常见的两层三跨地下结构处于强震(PGA < 0.3g)威胁概率较低的区域时,本文推荐选用190条天然地震动作为输入,当处于强震威胁概率较高的区域时,推荐输入280条天然地震动。

地铁车站结构  /  输入地震动  /  地震易损性  /  抗震性能

Based on the seismic fragility method,this paper designed a random sampling procedure to investigate the effect of different amounts of input ground motions on the seismic fragility curves of underground structures in the cloud method. Taking a shallow-buried subway station with two-story and three-span as the research object,a non-linear dynamic interaction finite element model of the soil-underground structure was established,and 350 natural ground motions were selected as inputs to calculate the seismic response. The seismic fragility curves were constructed based on PGA-IDR finally. The results show that the amount of input ground motions has a greater effect on the PGA thresholds for each performance level of underground structures when the amount is less than 190. When the amount is greater than 190,the seismic fragility curves for minor and moderate damage to underground structures are not affected by the amount;when the amount is greater than 280,the curves for extensive damage and collapse are negligibly affected by the amount. When the underground structure is in an area with a low probability of strong seismic threat,this paper recommends 190 natural ground motions as inputs,otherwise,it should be 280.

subway station structure  /  input ground motion  /  seismic fragility  /  seismic performance
庄海洋, 杨靖, 刘园园, 唐柏赞. 关于地下结构云图法地震易损性分析中输入地震动最优数量的探讨. 振动工程学报, 2025 , 38 (3) : 587 -594 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.03.015
Haiyang ZHUANG, Jing YANG, Yuanyuan LIU, Baizan TANG. Discussion on the optimum number of input ground motions in seismic fragility analysis of underground structures by cloud method[J]. Journal of Vibration Engineering, 2025 , 38 (3) : 587 -594 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.03.015
地震易损性分析是评价工程结构抗震性能的重要研究方法之一。通过计算特定地震动强度下工程结构超越特定破坏状态的条件概率绘制出工程结构的地震易损性曲线,从概率角度宏观描述其抗震性能,该方法已经在各类工程结构中得到广泛应用[1-3]。根据地震动强度指标(IM)可以预测工程结构的失效概率,对于工程结构日常的安全运营及震后的损伤评估具有重要参考意义。
地震易损性曲线通常分为经验易损性曲线及数值易损性曲线。就数值易损性曲线来讲,它的构建依赖于数值地震易损性分析得到的大量计算结果。云图法及条带法是获得大量计算数据的两种主流方法[4],两者的显著区别在于是否对所选择的天然地震动进行调幅。条带法主要基于增量动力分析方法(IDA),对选定的一定数量的地震动按照设定好的增量幅值进行调幅,从而得到不同强度等级的输入地震动。 ZHONG等[5]、ZHUANG等[3]及孔宪京等[6]采用条带法构建了地下结构及大坝的地震易损性曲线。相反,云图法是一种无需对地震动进行调幅的数值地震易损性分析方法。该方法通过筛选大量的天然地震动记录构成输入地震动数据库,最终完成工程结构的抗震性能计算。JALAYER等[7]基于贝叶斯方法改进了云图法,改进方法可有效考虑影响工程结构抗震性能的各种不确定因素;靳聪聪等[8]基于云图法探究了高石土坝的抗震可靠度;于晓辉等[9]提出了云图-条带法,以提升处理海量非线性计算结果的效率,程诗焱等[10]基于该方法探究了输入地震动持时对于结构地震易损性的影响。
地震易损性分析方法的计算工况总量取决于选择的地震动数量。就条带法而言,其总量等于选择的地震动数量乘以每条地震动确定的强度等级总级数。在针对地下结构的地震易损性分析中,采用IDA方法时,通常选取20条天然地震动作为输入[35]。 VAMVATSIKOS等[11]的研究也表明选取20条地震动作为输入足以考虑IDA方法中地震动的不确定性。采用云图法作为地下结构的地震易损性分析方法时,袁万城等[12]选择了75条天然地震动作为输入,于晓辉等[9]及代旷宇等[13]均选择了100条天然地震动作为输入,靳聪聪等[8]则选取了150条天然地震动作为输入。不同学者选取的地震动数量存在显著差异,而这也直接影响了最终构建的工程结构地震易损性曲线的精确性。
在基于概率的地震易损性分析中,通常假设结构损伤测度(DM)与地震动强度测度(IM)之间服从双对数线性分布,表达式为:
式中,ab均为拟合参数。
根据已有研究[35],地震易损性曲线可由对数正态概率分布函数计算:
式中,P (DS| IM = X)为特定地震动强度下工程结构发生特定破坏等级的条件概率;Φ(·)为标准正态累积分布函数;X为地震动强度等级;μ为DM中值对应的IM阈值,可通过式(1)计算得到;βtot由三个不确定因素组合计算得出,如下式所示:
式中,βC为地下结构不确定性,本文研究的是一种确定的结构,故忽略βCβDS设定为0.4,表示结构损伤定义引起的不确定性[14-15]βD为IM-DM双对数线性回归分析的标准差,可通过下式计算:
式中,N为计算工况的总数量。
本文工程结构的损伤参数DM选取为地下结构的层间位移角(IDR),地震动强度参数IM选取为地震动记录的峰值加速度峰值(PGA)。
本文研究的两层三跨矩形地铁地下车站结构的具体截面尺寸及配筋率参考文献[16]。为消除截断边界的影响,截断边界距离结构应大于结构宽度的5倍以上。考虑到计算效率,本文将模型场地的宽度定为200 m。如图1所示,本文建立的土-地下结构非线性动力相互作用有限元模型(SUSI)尺寸为200 m×80 m,场地土层参数见文献[16]。原型车站结构中,沿结构纵向每隔9.12 m布置中柱,因此将三维空间的车站结构等效为二维平面问题时须将中柱采用等刚度折减方法等效为沿结构纵向的0.8 m宽的墙体[16]。土体和结构的实体单元采用四节点平面应变减缩积分单元(CPE4R)模拟,钢筋采用两节点梁单元(B21)模拟。钢筋采用嵌入混凝土的方式进行模拟,忽略两者之间的滑移与分离。根据KUHLEMEYER等[17]的研究确定剪切波运动方向上单元网格的最大尺寸。本文最大截断频率设置为15 Hz,场地土层中最小的土层剪切波速为240 m/s,因此本文模型场地的单元网格尺寸在1~2 m之间,如图1所示。土体与地下结构间的法向接触采用“硬”接触,即接触面间发生拉应力时土体与结构之间产生分离,切向接触遵循库仑摩擦定律,即接触面间剪应力大于摩擦力时,土体将与地下结构产生切向滑动,摩擦系数设置为0.4。SUSI系统的边界条件转换见文献[16]。如图1所示,为记录模型场地地表的地震动记录,在距离地下结构侧墙60 m的地表处设置了地震动记录点。
本文采用LEE等[18]建立的非线性混凝土动力损伤本构,ABAQUS/Explicit内置了该混凝土损伤塑性模型(CDP)。车站结构的侧墙、板及梁采用C30混凝土浇筑,圆形中柱采用C40混凝土浇筑。混凝土本构模型参数见文献[16]。土体的非线性动本构模型采用ZHUANG等[19]建立的软土记忆性黏塑性嵌套本构模型,并通过Fortran软件进行程序编写以实现与ABAQUS软件对接。该模型基于土体的广义塑性理论,采用等向硬化和随动硬化相结合的硬化模量场理论,建立了一个总应力增量形式的土体黏塑性动本构模型。已通过动三轴试验验证了该本构土体模型的可靠性,并与常用的等效线性本构模型对自由场地震反应的分析结果进行了对比分析,验证了该本构模型的可靠性和优越性[20]。模型具体参数见文献[1620]。
本文选取的天然地震动均下载自太平洋地震工程中心[21],由于云图法不对天然地震动进行调幅,本文考虑了所选择的天然地震动的峰值加速度强度的分布,避免出现输入的地震动强度多数偏大或偏小的情况。图2(a)给出了峰值加速度(PA)的分布,350条天然地震动的PA均值为0.252g,0.1g~0.4g的地震动记录有242条,<0.1g的有48条,>0.4g的有60条。此外,本文研究对象是地下结构,天然地震动记录是从有限元模型底部的基岩输入的,因此在选择输入地震动的同时,本文也考虑了采集天然地震动记录的场地条件,在兼顾PA分布的同时,尽可能选取场地30 m土层的等效剪切波速Vs30大于300 m/s的场地记录到的天然地震动。图2(b)给出了这些天然地震动记录采集场地的Vs30分布,其中超过300 m/s的有206个。此外,本文350条天然地震动共选自180个台站,这些台站断层距在20 km内的有110个,20~60 km内的有62个。天然地震动记录从有限元模型场地底部基岩水平向输入,为与地表记录到的地震动记录的峰值加速度PGA区分,特此定义基岩输入峰值加速度为PBA(peak bedrock acceleration)。
图3首先给出对照组的分析结果,对照组即全部350条输入地震动的计算结果。按照YANG等[22]的研究,基于IDR的两层三跨地铁车站结构抗震性能等级量化体系如表1所示。本文使用各抗震性能等级限值的中值作为各级的阈值,对于倒塌的IDR阈值确定为1.2%。图3(a)给出了PGA-IDR的双对数线性回归分析结果,根据线性拟合公式及IDR阈值,即可计算出各抗震性能等级的PGA阈值(μ)。如表1所示,轻微破坏至倒塌的μ值分别为0.355g、0.447g、0.556g及0.711g。最终,可根据式(2)计算出该地下结构的地震易损性曲线,如图3(b)所示。
本文设置的输入地震动数量最少为50条,在350条地震动中随机抽取50条作为输入地震动组合,那么组合的数量是巨大的,因此有必要明确适宜的样本组数量(在固定的输入地震动数量下抽取i次,即得到该数量下i个样本组),避免在固定的输入地震动数量下抽取的样本组不具有代表性。图4给出了本文确定样本组数量的方法。在输入350条天然地震动计算得到的地下结构IDR数据库中,每次随机抽取50个IDR数据并计算该样本组数据的均值及标准差,重复这个过程i次,即可得到i个样本组的均值及标准差,进一步计算出i个样本组的均值的变异系数及标准差的变异系数。i次抽取过程结束后,即开始重复抽取i+1次,最终可以通过变异系数的波动情况观察固定输入地震动数量下样本组数量的影响。一组数据的变异系数计算如下式所示:
式中,Cv为变异系数;为该组数据的均值,SD为该组数据的标准差。
本文设置的样本组数量最少为20,然后样本组数量以1为增量,递增至1500,图5给出了不同样本组数量下变异系数的结果。从图5中可以发现,当样本组数量过少时,无论是均值或是标准差的变异系数均波动较大,当样本组数量超过400时,均值及标准差的变异系数均在有限范围内波动,这表明在随机抽取50条输入地震动的计算结果时,随机抽取的样本组数量超过400组即足以代表该地震动数量下地下结构IDR的幅值分布水平。最终,本文将样本组数量i设置为500。
由式(2)可知,工程结构的地震易损性曲线是直接由各抗震性能等级所对应的IM阈值计算得来的,因此对于输入地震动数量对构建工程结构地震易损性曲线的影响,本文直接探究输入地震动数量对各抗震性能等级PGA阈值(μ)的影响。图6给出了探究地震动数量影响的流程图。首先随机抽取k对PGA-IDR数据进行双对数线性回归分析,进而计算得到对应各抗震性能等级的μ值,上述过程会重复500次,最终得到500组k条地震动输入计算得到的地下结构各抗震性能等级的μ值,进一步计算上述500组各抗震性能等级μ值的均值及标准差。k条输入地震动计算完成后,设定k的增量为5,开始随机抽取并计算k+5条输入地震动,最终计算至350条,本文中k的起始值设置为50。
图7给出了地下结构各抗震性能等级μ值的均值及标准差随着输入地震动数量变化的曲线。对于μ值的均值,当输入地震动数量少于190条时,各抗震性能等级μ值受输入地震动数量的影响明显,围绕对照组μ值波动幅值较大,尤其是在严重破坏及倒塌两个等级下,μ值的误差显著;当输入地震动数量大于190条时,μ值波动范围收窄,基本围绕对照组μ值小范围波动,因此根据图7可大致确定输入地震动数量不宜小于190条。由图7μ值的标准差也可以发现,随着输入地震动数量的增加,500个样本组μ值的标准差会逐渐减小,在输入地震动数量小于190条时,标准差数值下降较快;当大于190条时,标准差呈现线性减小趋势。即输入地震动数量小于190条时,地震动数量对各抗震性能等级μ值的影响较大。
图8给出了随机抽取190条输入地震动计算结果的500个样本组的μ值。可以发现,轻微破坏及中度破坏的μ值均围绕对照组μ值小范围波动,而严重破坏及倒塌则误差较大,这佐证了图7中的结果。为进一步探讨输入地震动数量对于地震易损性曲线的影响,本文将从固定输入地震动数量的500个样本组中选出μ值偏离对照组最大的一组样本构建地下结构的地震易损性曲线,进而直接对比曲线误差。由图78可知,地震动数量不宜小于190条,且倒塌等级对应的μ值误差最大,因此将从输入190条地震动至输入300条地震动各自对应的500组样本中挑选倒塌等级μ值偏离最大的样本组构建地震易损性曲线。
表2给出了随机抽取190条地震动至300条地震动各自对应的样本组的结果及其与对照组的误差率,190#~300#为样本组,350#为对照组。轻微破坏及中度破坏的μ值误差率最小,均在3.5%以内。当输入地震动数量大于280条时,轻微破坏的μ值误差率可忽略不计,中度破坏误差率在1.2%以内;严重破坏及倒塌的μ值误差率较大,尤其是输入地震动数量较少时,误差率超过了4%。图9进一步给出了上述样本组构建的地下结构的地震易损性曲线对比。可以看出,基于不同输入地震动数量所构建的轻微破坏等级的地震易损性曲线基本一致;其他抗震性能等级的地震易损性曲线在PGA小于0.3g时预测概率基本一致,随着抗震性能等级及PGA的提高,对破坏概率的预测误差逐渐显现,尤其是输入地震动数量较少的样本组所构建的曲线。
图10给出了不同曲线各抗震性能等级破坏概率与对照组预测概率的最大误差,该最大误差由下式计算:
式中,Pdif为最大破坏概率预测误差;P (DS| IM = X)i为在特定地震动强度下超特定抗震性能等级的条件概率,i为第i条地震易损性曲线;P (DS| IM = X)350#为对照组曲线的破坏概率。
轻微破坏等级下,无论是基于多少条输入地震动所构建的地震易损性曲线,其对于轻微破坏的预测概率均与对照组误差不大,不超过1.25%,当输入地震动数量超过280条,误差仅在0.5%以内,可忽略不计。对于中度破坏的预测概率,最大预测误差为2.22%,当输入地震动数量超过280条,最大预测误差控制在1%以内。相比于前两个抗震性能等级,严重破坏及倒塌的最大预测误差则相对较大,受输入地震动数量的影响显著。但随着输入地震动数量的增加,最大预测误差逐渐减小,当输入地震动数量超过280条时,严重破坏的最大预测误差可控制在1.5%以内,倒塌则在2.5%以内。上述误差结果表明,当输入地震动数量大于190条时,轻微破坏及中度破坏的预测概率受输入地震动数量的影响大不,地震易损性曲线基本与对照组一致,预测概率的误差极小,而严重破坏及倒塌的预测概率受输入地震动数量的影响则相对较大,当输入地震动数量超过280条时,其预测误差可明显改善。
研究结果表明,当从数据库中随机抽取固定数量的输入地震动计算结果时,为保证所抽取的样本组能够代表该输入地震动数量下计算结果的客观性,应保证样本组数量在400组以上。当输入地震动数量大于190条时,对轻微破坏及中度破坏的最大预测误差极低,而严重破坏及倒塌的最大预测误差则相对较大;在输入地震动数量超过280条时,该误差会明显改善。本文建议当所研究的地下结构位于强震(PGA<0.3g)威胁概率较低的区域时,可适当减少其地震易损性分析时所输入的地震动数量,推荐输入190条天然地震动;而当地下结构位于强震威胁概率较大的区域时,建议输入不少于280条天然地震动。
此外,需要说明的是,本文所选取的350条天然地震动并未针对近、远场等各类特性地震动进行筛选,并且是针对单一工程场地开展的分析,因此本文结论尚存在一定局限性。但所提出的随机抽取程序的思路可为相关研究提供参考。
  • 国家自然科学基金资助项目(51978333)
  • 南京工业大学优秀博士学位论文培育计划资助项目
  • 江西省主要学科学术和技术带头人培养计划项目(20204BCJL23032)
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2025年第38卷第3期
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doi: 10.16385/j.cnki.issn.1004-4523.2025.03.015
  • 接收时间:2023-02-28
  • 首发时间:2026-02-11
  • 出版时间:2025-03-10
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  • 收稿日期:2023-02-28
  • 修回日期:2023-04-27
基金
国家自然科学基金资助项目(51978333)
南京工业大学优秀博士学位论文培育计划资助项目
江西省主要学科学术和技术带头人培养计划项目(20204BCJL23032)
作者信息
    1.华东交通大学土木建筑学院,江西 南昌 330013
    2.南京工业大学岩土工程研究所,江苏 南京 210009

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庄海洋(1978—),男,博士,教授。E-mail:
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2种不同金属材料的力学参数

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种数
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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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