Article(id=1241442315617759469, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241442313185063097, articleNumber=null, orderNo=null, doi=10.3963/j.issn.1001-487X.2023.01.024, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1664467200000, receivedDateStr=2022-09-30, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773912512925, onlineDateStr=2026-03-19, pubDate=1677600000000, pubDateStr=2023-03-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773912512925, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773912512925, creator=13701087609, updateTime=1773912512925, updator=13701087609, issue=Issue{id=1241442313185063097, tenantId=1146029695717560320, journalId=1240670690148397066, year='2023', volume='40', issue='1', pageStart='1', pageEnd='220', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773912512346, creator=13701087609, updateTime=1773912765519, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241443375145079400, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241442313185063097, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241443375145079401, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241442313185063097, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=177, endPage=184, ext={EN=ArticleExt(id=1241442315873612027, articleId=1241442315617759469, tenantId=1146029695717560320, journalId=1240670690148397066, language=EN, title=Grey Correlation Analysis of Damage Factors of Prefabricated Pier under Explosion Load, columnId=1240702076553065119, journalTitle=Blasting, columnName=BLASTING SAFETY, runingTitle=null, highlight=null, articleAbstract=

Prefabricated piers are widely used in the field of bridge construction and are often affected by accidental explosions or terrorist attacks. In order to study the influence law of the damage factors of prefabricated bridge piers under explosion load, a numerical model of the prefabricated bridge piers under near-field explosion load has been established by ANSYS. Based on the residual bearing capacity of bridge piers, the damage parameter D is proposed as the anti-explosion index. The influence of five damage factors, including the explosive equivalent, the distance from the explosion center, the initial prestress, the number of segments and the setting of shear keys, on the damage degree of bridge piers is analyzed. On this basis, grey correlation analysis method is used to measure the degrees of correlation and contribution among the damage factors. The results show that the comprehensive reduction rates of failure parameter D are 32.1% and 29.6% by increasing the initial prestress and setting shear keys between segments, which can effectively reduce the damage of the piers and have a good correlation with the blast resistance of prefabricated piers. However, increasing the shear key height and segment number to 12% and 7.2% has a small effect on pier damage. The order from largest to smallest of the five factors in the correlation degree on the damage of the fabricated bridge piers under blast loading is: TNT equivalent, blast center distance, initial tensile prestress, shear key setting and segment number. In the anti-explosion design of prefabricated bridge piers, the factors of large correlations such as increasing the initial tensile prestress and setting shear keys can be given priority. The grey correlation analysis method has certain reference value for the analysis of damage factors of prefabricated bridge piers under explosive load.

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装配式桥墩在桥梁施工领域得到广泛的应用,常受偶然爆炸或恐怖袭击的打击影响。为研究爆炸荷载下装配式桥墩损伤因素的影响规律,采用ANSYS/Workbench建立了近场爆炸荷载作用下的装配式桥墩数值模型,基于桥墩剩余承载力,提出以破坏参数D作为抗爆性指标,以炸药当量、爆心距离、初始预应力大小、节段数和剪力键的设置为损伤因素,分析了5种因素对桥墩损伤程度影响。在此基础上,利用灰色关联分析法衡量爆炸荷载下装配式桥墩损伤因素之间关联度的指标与贡献度。结果表明:增大初始预应力、节段间设置剪力键其破坏参数D的综合降低率为32.1%、29.6%,均能有效降低墩柱的损伤,与装配式桥墩抗爆受损有良好的关联性;而增加剪力键高度和节段数为12%、7.2%,对墩柱损伤影响较小;5种因素对爆炸荷载下装配式桥墩损伤影响的关联度从大到小为:TNT当量、爆心距离、初张拉预应力、剪力键的设置、节段数量。装配式桥墩抗爆设计中,可优先考虑提高初张拉预应力大小、设置剪力键等关联度较大的因素,灰色关联分析法对爆炸荷载下装配式桥墩损伤因素分析具有一定的参考性。

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姜天华(1971-),男,博士、教授,从事桥梁结构理论及工程应用研究,(E-mail)

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姜天华(1971-),男,博士、教授,从事桥梁结构理论及工程应用研究,(E-mail)

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姜天华(1971-),男,博士、教授,从事桥梁结构理论及工程应用研究,(E-mail)

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(in Chinese), articleTitle=Experimental study on the ground reflection overpressure of explosive blast shock wave in air, refAbstract=null), Reference(id=1241442342159315105, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, doi=null, pmid=null, pmcid=null, year=2017, volume=null, issue=null, pageStart=107, pageEnd=154, url=null, language=null, rfNumber=[16], rfOrder=23, authorNames=刘思峰, journalName=灰色系统理论及其应用, refType=null, unstructuredReference=刘思峰. 灰色系统理论及其应用[M]. 北京: 科学出版社, 2017: 107-154., articleTitle=null, refAbstract=null), Reference(id=1241442342230618274, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, doi=null, pmid=null, pmcid=null, year=2017, volume=null, issue=null, pageStart=107, pageEnd=154, url=null, language=null, rfNumber=[16], rfOrder=24, authorNames=LIU Si-feng, journalName=Grey Systems Theory and its Application, refType=null, unstructuredReference=LIU Si-feng. Grey Systems Theory and its Application[M]. Beijing: Science Press, 2017: 107-154., articleTitle=null, refAbstract=null), Reference(id=1241442342364836006, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, doi=null, pmid=null, pmcid=null, year=2013, volume=42, issue=2, pageStart=309, pageEnd=317, url=null, language=null, rfNumber=[17], rfOrder=25, authorNames=WANG Zheng-xin, journalName=Kybernetes, refType=null, unstructuredReference=WANG Zheng-xin. Correlation analysis of sequences with interval grey numbers based on the kernel and greyness degree[J]. 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Main Parameters of the Concrete Material Model

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密度ρ/(kg·m-3泊松比杨氏模量/GPa压力硬化系数N单轴抗压强度/MPa
2.40.232.50.6126.8
), ArticleFig(id=1241442336929017903, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=CN, label=表1, caption=

混凝土材料模型主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
密度ρ/(kg·m-3泊松比杨氏模量/GPa压力硬化系数N单轴抗压强度/MPa
2.40.232.50.6126.8
), ArticleFig(id=1241442337067429944, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=EN, label=Table 2, caption=

Main parameters of the steel material model

, figureFileSmall=null, figureFileBig=null, tableContent=
密度ρ/(kg·m-3泊松比杨氏模量/GPa屈服应力/MPa切线模量/MPa
7.850.32102651180
), ArticleFig(id=1241442337205841980, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=CN, label=表2, caption=

钢筋材料模型主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
密度ρ/(kg·m-3泊松比杨氏模量/GPa屈服应力/MPa切线模量/MPa
7.850.32102651180
), ArticleFig(id=1241442337319088190, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=EN, label=Table 3, caption=

Main Parameters of the TNT Material Model

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密度ρ/(kg·m-3爆速D/(mm·ms-1爆压PCJ/GPaE0/(J·mm-3V0
1.636 717.4217 0001
), ArticleFig(id=1241442337444917314, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=CN, label=表3, caption=

TNT材料模型主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
密度ρ/(kg·m-3爆速D/(mm·ms-1爆压PCJ/GPaE0/(J·mm-3V0
1.636 717.4217 0001
), ArticleFig(id=1241442337553969221, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=EN, label=Table 4, caption=

Main parameters of the air material model

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密度ρ/(kg·m-3参数C0参数C1~C3C6参数C4~C5E0/(J·mm-3
1.3-0.100.40.25
), ArticleFig(id=1241442337683992651, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=CN, label=表4, caption=

空气材料模型主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
密度ρ/(kg·m-3参数C0参数C1~C3C6参数C4~C5E0/(J·mm-3
1.3-0.100.40.25
), ArticleFig(id=1241442337834987601, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=EN, label=Table 5, caption=

Grey correlation analysis parameters

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序号X1TNT当量/kgX2爆心距离/mX3轴压比X4节段数量X5剪力键高度/mX0破坏参数
150.30.10500.109
2100.30.10500.327
3150.30.10500.616
4200.30.10500.904
5200.60.10500.764
6200.90.10500.682
7201.20.10500.633
8200.30.15500.688
9200.30.20500.503
10200.30.10300.974
11200.30.10600.856
12200.30.1050.040.687
13200.30.1050.080.646
14200.30.1050.120.633
), ArticleFig(id=1241442337990176853, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241442315617759469, language=CN, label=表5, caption=

灰色关联分析参数

, figureFileSmall=null, figureFileBig=null, tableContent=
序号X1TNT当量/kgX2爆心距离/mX3轴压比X4节段数量X5剪力键高度/mX0破坏参数
150.30.10500.109
2100.30.10500.327
3150.30.10500.616
4200.30.10500.904
5200.60.10500.764
6200.90.10500.682
7201.20.10500.633
8200.30.15500.688
9200.30.20500.503
10200.30.10300.974
11200.30.10600.856
12200.30.1050.040.687
13200.30.1050.080.646
14200.30.1050.120.633
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爆炸荷载下装配式桥墩损伤因素灰色关联分析
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姜天华 a, b , 高作能 a, b , 管建成 a, b , 赵新洲 a, b , 黄雯 a, b
爆破 | 安全与管理 2023,40(1): 177-184
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爆破 | 安全与管理 2023, 40(1): 177-184
爆炸荷载下装配式桥墩损伤因素灰色关联分析
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姜天华a, b , 高作能a, b, 管建成a, b, 赵新洲a, b, 黄雯a, b
作者信息
  • a.武汉科技大学 城市建设学院,武汉 430065
  • b.武汉科技大学 高性能工程结构研究院,武汉 430065
  • 姜天华(1971-),男,博士、教授,从事桥梁结构理论及工程应用研究,(E-mail)

Grey Correlation Analysis of Damage Factors of Prefabricated Pier under Explosion Load
Tian-hua JIANGa, b , Zuo-neng GAOa, b, Jian-cheng GUANa, b, Xin-zhou ZHAOa, b, Wen HUANGa, b
Affiliations
  • a.Urban Construction College, Wuhan University of Science and Technology, Wuhan 430065, China
  • b.Institute of High Performance Engineering Structure, Wuhan University of Science and Technology, Wuhan 430065, China
出版时间: 2023-03-01 doi: 10.3963/j.issn.1001-487X.2023.01.024
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装配式桥墩在桥梁施工领域得到广泛的应用,常受偶然爆炸或恐怖袭击的打击影响。为研究爆炸荷载下装配式桥墩损伤因素的影响规律,采用ANSYS/Workbench建立了近场爆炸荷载作用下的装配式桥墩数值模型,基于桥墩剩余承载力,提出以破坏参数D作为抗爆性指标,以炸药当量、爆心距离、初始预应力大小、节段数和剪力键的设置为损伤因素,分析了5种因素对桥墩损伤程度影响。在此基础上,利用灰色关联分析法衡量爆炸荷载下装配式桥墩损伤因素之间关联度的指标与贡献度。结果表明:增大初始预应力、节段间设置剪力键其破坏参数D的综合降低率为32.1%、29.6%,均能有效降低墩柱的损伤,与装配式桥墩抗爆受损有良好的关联性;而增加剪力键高度和节段数为12%、7.2%,对墩柱损伤影响较小;5种因素对爆炸荷载下装配式桥墩损伤影响的关联度从大到小为:TNT当量、爆心距离、初张拉预应力、剪力键的设置、节段数量。装配式桥墩抗爆设计中,可优先考虑提高初张拉预应力大小、设置剪力键等关联度较大的因素,灰色关联分析法对爆炸荷载下装配式桥墩损伤因素分析具有一定的参考性。

装配式桥墩  /  灰色关联分析  /  爆炸荷载  /  损伤因素分析  /  数值模拟

Prefabricated piers are widely used in the field of bridge construction and are often affected by accidental explosions or terrorist attacks. In order to study the influence law of the damage factors of prefabricated bridge piers under explosion load, a numerical model of the prefabricated bridge piers under near-field explosion load has been established by ANSYS. Based on the residual bearing capacity of bridge piers, the damage parameter D is proposed as the anti-explosion index. The influence of five damage factors, including the explosive equivalent, the distance from the explosion center, the initial prestress, the number of segments and the setting of shear keys, on the damage degree of bridge piers is analyzed. On this basis, grey correlation analysis method is used to measure the degrees of correlation and contribution among the damage factors. The results show that the comprehensive reduction rates of failure parameter D are 32.1% and 29.6% by increasing the initial prestress and setting shear keys between segments, which can effectively reduce the damage of the piers and have a good correlation with the blast resistance of prefabricated piers. However, increasing the shear key height and segment number to 12% and 7.2% has a small effect on pier damage. The order from largest to smallest of the five factors in the correlation degree on the damage of the fabricated bridge piers under blast loading is: TNT equivalent, blast center distance, initial tensile prestress, shear key setting and segment number. In the anti-explosion design of prefabricated bridge piers, the factors of large correlations such as increasing the initial tensile prestress and setting shear keys can be given priority. The grey correlation analysis method has certain reference value for the analysis of damage factors of prefabricated bridge piers under explosive load.

prefabricated piers  /  gray correlation analysis  /  explosion load  /  analysis of damage factors  /  numerical simulation
姜天华, 高作能, 管建成, 赵新洲, 黄雯. 爆炸荷载下装配式桥墩损伤因素灰色关联分析. 爆破, 2023 , 40 (1) : 177 -184 . DOI: 10.3963/j.issn.1001-487X.2023.01.024
Tian-hua JIANG, Zuo-neng GAO, Jian-cheng GUAN, Xin-zhou ZHAO, Wen HUANG. Grey Correlation Analysis of Damage Factors of Prefabricated Pier under Explosion Load[J]. Blasting, 2023 , 40 (1) : 177 -184 . DOI: 10.3963/j.issn.1001-487X.2023.01.024
装配式桥墩为当前桥梁建设领域重要的受力构件,其在爆炸作用下的损伤破坏直接影响着桥梁整体的安全性和稳定性,严重时将导致桥梁整体倒塌[1]。因此,进行爆炸荷载下装配式桥墩损伤因素的研究具有重要的工程意义。
已有学者通过数值模拟精确分析爆炸荷载下建筑结构柱的倒塌与损伤因素[2,3],但建筑结构柱具有连续失效倒塌性,与桥梁墩柱损伤分析有显著区别。SHI首次提出采用剩余承载力为破坏参数来衡量爆炸荷载下钢筋混凝土柱的损伤程度[4],给出了配箍率、纵筋配筋率和长细比不同时柱的损伤指标。吴亮利用ANSYS对钢筋混凝土桥墩在爆炸作用下的抗爆性能展开了研究[5],以动力响应与损伤分析为标准,改变比例距离、配筋率、箍筋间距等不同参数来研究其对柱体抗爆性能的影响。吴文燕建立了爆炸作用影响下钢筋混凝土柱有限元模型[6],以柱剩余承载力作为破坏参数,得到了箍筋配筋率、炸药当量、混凝土强度、纵筋配筋率、爆源距离5种损伤因素的灰色关联度。而钢筋混凝土柱不同于装配式桥墩,后者因墩身不连续而抗剪能力较弱。Liu对装配式桥墩进行了缩尺现场试验[7],研究了在近场爆炸荷载作用下的损伤因素和破坏模式。杨旭分析了爆炸荷载下圆形截面装配式桥墩节段长细比、初始预应力水平及桥墩体系的损伤因素规律[8]。Li基于剩余承载力定义损伤准则[9],研究张拉预应力筋和设置耗能钢筋的装配式桥墩损伤因素规律。以上研究将装配式桥墩损伤因素与墩柱剩余承载力建立了联系,但针对基于剩余承载力的装配式桥墩损伤因素关联性分析的研究较少。
基于ANSYS/Workbench建立装配式桥墩的三维实体模型,通过对现有爆炸试验进行数值模拟的验证。现基于炸药当量、爆心距离、初始预应力大小、节段数量、剪力键的设置5种因素,以剩余承载力为抗爆性指标,利用灰色关联分析法对爆炸荷载下装配式桥墩的损伤因素展开分析,旨在寻找出评价装配式桥墩抗爆性能的显著性指标,可为装配式桥墩的抗爆性能研究提供参考。
基于ANSYS/Workbench建立装配式桥墩的三维实体分离式模型,包括钢筋、混凝土、炸药和空气4个部分,基于Nikhil对受爆炸影响的桥梁倒塌的调查[10],选取某城市高架桥桥墩,建立数值模拟如图1所示,桥墩高3.0 m,截面尺寸0.4 m×0.4 m,混凝土强度等级C40,纵筋选用12根ϕ 20 mm钢筋,箍筋选用6根ϕ 10 mm钢筋,间距100 mm,混凝土保护层厚度取30 mm。剪力键尺寸为160 mm×160 mm×80 mm的装配式桥墩有限元模型及带剪力键节段局部放大图如图2所示。
预应力钢束的受拉、受压边缘的距离为L/4=100 mm。添加稳态热模块实现用降温法施加初始预应力[11],预应力筋通过降温收缩产生相应的拉力利用锚具作用到桥墩上。混凝土、空气及炸药采用实体单元,钢筋采用梁单元。混凝土网格、钢筋网格和空气网格均设为25 mm,炸药与空气设置为共节点连接[12]。混凝土和钢筋采用Lagrange算法描述,炸药和空气采用ALE(Arbitrary LagrangeEuler)算法实现装配式混凝土桥墩与空气爆炸冲击波的流固耦合动态分析,节段之间用无滑移摩擦接触,根据文献[13]的取值建议,节段间静摩擦、动摩擦和指数衰减因数分别取1.0、0.8、0.5。为避免边界反射对解域的影响,设置阻抗边界条件来模拟无限空间。考虑一般装配式桥墩的实际情况受力特点,在墩顶施加10%的竖向荷载预压力,且考虑桥墩自重影响。
钢筋和混凝土在爆炸荷载下,其物理力学性能与静载条件下有明显区别,将钢筋与混凝土最大主应变作为失效算法的判据,最大主应变设置分别为0.15和0.25。
针对混凝土在爆炸作用的高应变率及大变形,以*MAT_JOHNSON_HOLMQUIST CONCRETE[14]模拟C40混凝土;针对钢材在爆炸作用下的高动态屈服强度及瞬时应力,选用非线性(PKE)材料模型*MAT_PLASTIC_KIN_EMATIC[13],具体材料参数如表1表2所示。
TNT选用*MAT_HIGH_EXPLOSIVE_BURN高爆材料,状态方程选用*EOS_JWL[14];空气简化为无黏性理想气体,爆炸冲击波的膨胀假设为等熵绝热过程,材料选用*MAT_NULL,状态方程选用*EOS_LINEAR_POLYNOMINAL[15]。具体材料参数如表3表4所示。
Liu通过近场爆炸实验研究了装配式柱在爆炸荷载作用下的损伤特征[7],实验中使用TNT炸药在距离柱脚0.3 m处起爆,实验布置如图3所示。建立原尺寸数值模型,如图4所示,对比Liu爆炸实验中装配式柱残余位移和破坏模式,验证数值模拟算法的正确性。
图5所示,从实验破坏形态中可看出混凝土柱底表面出现表皮脱落,迎爆面破坏最严重残留少许混凝土保护层,混凝土柱整体位移不明显,数值模拟破坏结果中混凝土保护层脱落和桥墩变形与实验结果基本一致。
混凝土柱沿高度方向的残余位移曲线如图6所示,可看出混凝土柱的数值模拟最大残余位移为67 mm,最小残余位移6 mm,而实验结果最大残余位移为63 mm,最小残余位移5 mm,综合差异仅为5.27%。综上,可认为此数值模型、参数及其算法是有效的。
Shi基于柱剩余承载力的损伤程度评价方法,提出了破坏参数D
式中:N′为构件在爆炸荷载作用后的竖向剩余承载力,可通过试验或数值模拟得到。以5 kg TNT爆炸荷载下桥墩的损伤模型为例,爆炸响应完成后桥墩损伤模型如图7所示,继续对桥墩进行重启动,墩顶逐级施加荷载,直至墩破坏,即可求出墩剩余承载力N′。N为构件未遭受爆炸荷。
载前的竖向承载力,可通过下式得到[4]
式中:为混凝土的轴心抗压强度;fy为纵筋的屈服强度;AG为桥墩的截面面积;AS为纵筋的总截面面积。可知fy=400 MPa、AG=0.16 m2AS=0.0038 m2,求得N=5078.2 kN。
改变TNT当量可得墩柱剩余承载力N′分别为4 524.7 kN、3 417.6 kN、1 950 kN、487.5 kN,破坏参数D分别为0.109、0.327、0.616、0.904。变化曲线如图8所示。10 kg、15 kg和20 kg较上一级增长量分别为0.218、0.289、0.288,增长率分别为200%、88.4%和46.8%。可知,炸药当量对装配式桥墩损伤影响较大,破坏参数的增长量、增长率相对较高。
不同炸药当量下通过改变爆心距离,可得破坏参数D的变化曲线,如图9所示。0.6 m、0.9 m和1.2 m相较于上一级破坏参数D的综合降低率分别为13.2%、10.6%和8.6%。可知,炸药当量增加,破坏参数降低量随之增加,且爆心距离对大当量爆炸荷载下桥墩损伤降低量的影响较为显著。
研究初张拉预应力为640 kN、960 kN、1250 kN(轴压比0.1、0.15、0.2)的装配式桥墩在不同炸药当量下的损伤程度,破坏参数D的变化曲线如图10所示。轴压比0.15相较于0.1破坏参数D的综合降低率为29.1%,轴压比0.2相较于0.15破坏参数D的综合降低率为35.1%。可知,轴压比增加,破坏参数D显著减小,由于装配式节段间产生相对摩擦滑动,施加初始预应力会增加节段间的应力从而增加摩擦力,提高装配式桥墩的能耗与抗爆性能,且影响较大。
装配式桥墩实际为5节段,为研究节段数量对桥墩损伤的影响,分别设置3节段、5节段和6节段墩柱,分析3种节段数在不同炸药当量下的损伤程度,破坏参数D的变化曲线如图11所示。5节段相较于3节段破坏参数D的综合降低率为15.9%,6节段相较于5节段破坏参数D的综合降低率为8.2%。可知,随节段数量增加,破坏参数D的降低率逐渐减小,降低率和降低量较小且变化不大,增加节段数量能提高桥墩抗爆性能,但影响较小。
研究不设剪力键、剪力键高度0.04 m、0.08 m和0.12 m四种工况在不同炸药当量下的损伤程度,破坏参数D的变化曲线如图12所示。设置0.04 m剪力键相较于不设剪力键破坏参数D的综合降低率为29.6%,0.08 m和0.12 m相较于上一级破坏参数D的综合降低率分别为8.3%和6.0%。可知,增设剪力键可以有效降低破坏参数D的值,对桥墩抗爆性能影响较大。而剪力键高度增加,破坏参数D逐渐减小,降低率变化不大,对桥墩抗爆性能影响较小。
灰色关联分析法是衡量灰色系统内部影响因素之间关联度的指标,基于灰色关联的影响因素来确定对系统的贡献度。通过比较系统中各影响因素的灰色关联度大小,可确定各因素与参考变量之间的主次关系,进而掌握事件的主要特征[16,17]。灰色关联分析法一般步骤如下。
(1)选择系统特征序列和关联因素序列。以破坏参数D作为系统特征变量X0。以炸药当量、爆心距离、初张拉预应力、节段数和剪力键的设置为关联因素变量Xii=1、2、3、4、5)。
系统特征数据序列
关联因素数据序列
式中:n为样本容量;i为第i个关联因素。
(2)去量纲化处理。系统中各因素的数据量纲不同,直接进行计算将得到不准确的结论,需对影响因素做量化研究,通过均值像计算对关联因素序列进行去量纲化处理
式中:XiD1为均值像;Xik)为第k次试验第i个关联因素变量值。
(3)计算差序列。求出每个关联因素序列与系统行为序列之间的差序列,及两极最小差与最大差。
差序列计算
最小差计算
最大差计算
(4)计算关联系数
式中:ε为分辨系数,在0~1之间取值,一般取0.5。
(5)计算关联度
式中:γ0ik)为第i个损伤因素Xi与特征变量X0的灰色关联度,其数值越大,代表XiX0的影响越大。
以破坏参数D作为系统特征变量,炸药当量、爆心距离、初始预应力大小、节段数量、剪力键的设置5种损伤因素作为关联因素变量,将模拟结果中选取的14组数据进行汇总,如表5所示。通过式(3)~(10)对表5数据进行处理,得到各因素对装配桥墩损伤的影响程度,结果如图13所示。
图13可看出,装配式桥墩损伤的五个损伤因素的关联度从大到小为:TNT当量、爆心距离、初张拉预应力、剪力键的设置、节段数量。初张拉预应力和设置剪力键的灰色关联度较好,表明两者可以作为装配式桥墩抗爆性能的重要评价指标。由于爆炸当量和爆心距离是不可控因素,增大初始张力预应力和设置剪力键可以显著减少桥墩的破坏,增加节段数对桥墩的破坏影响相对较小。
1)炸药当量和爆心距离是影响装配式桥墩抗爆性能最直接的因素,同是不可控因素。增大初张拉预应力、设置剪力键、增加节段数均能提高装配式桥墩的抗爆性能,可进一步为装配式桥墩的抗爆设计提供参考。
2)初张拉预应力、设置剪力键与装配式桥墩抗爆受损的关联性较好,可用于装配式桥墩抗爆性能损伤评价,在实际工程中可重点考虑与装配式桥墩关联性较大的损伤因素。增加剪力键高度、节段数对墩柱损伤影响较小。
3)灰色关联分析可准确求得各损伤因素对于装配式桥墩之间的主次关系,且样本数量与规律的随机性对结果不产生影响,能确保定量和定性结果的一致性,进而得到爆炸荷载下装配式桥墩损伤的主要影响因素,提出以剩余承载力作为破坏参数的灰色关联分析法可作为爆炸荷载下装配式桥墩损伤因素分析的参考。
  • 东南沿海工程结构防灾减灾福建省高校工程研究中心开放课题(2019002)
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2023年第40卷第1期
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doi: 10.3963/j.issn.1001-487X.2023.01.024
  • 接收时间:2022-09-30
  • 首发时间:2026-03-19
  • 出版时间:2023-03-01
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  • 收稿日期:2022-09-30
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东南沿海工程结构防灾减灾福建省高校工程研究中心开放课题(2019002)
作者信息
    a.武汉科技大学 城市建设学院,武汉 430065
    b.武汉科技大学 高性能工程结构研究院,武汉 430065
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2种不同金属材料的力学参数

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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
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