Article(id=1149780473641132459, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149780466032669506, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2402766, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1713196800000, receivedDateStr=2024-04-16, revisedDate=1735488000000, revisedDateStr=2024-12-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1752058626804, onlineDateStr=2025-07-09, pubDate=1744041600000, pubDateStr=2025-04-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752058626804, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752058626804, creator=13701087609, updateTime=1752058626804, updator=13701087609, issue=Issue{id=1149780466032669506, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='10', pageStart='3969', pageEnd='4395', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752058624990, creator=13701087609, updateTime=1768456644259, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218558743898411553, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149780466032669506, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218558743898411554, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149780466032669506, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3986, endPage=3995, ext={EN=ArticleExt(id=1149780474052174257, articleId=1149780473641132459, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Prediction and Factor Evaluation of Perforation Velocity of Steel-Concrete-Steel Slab against Missile Impact, columnId=1156264149949735860, journalTitle=Science Technology and Engineering, columnName=Papers·Mechanics, runingTitle=null, highlight=null, articleAbstract=

In order to predict perforation velocity of SCS (steel-concrete-steel) slab against missile impact and obtain influence sequence of structural factors of SCS slab on the perforation velocity, a dimensionless equation of the perforation velocity was established and a prediction model was obtained based on dimensional analysis and artificial neural network. Orthogonal experiment design was used to determine finite element calculation, and the influence degree of 7 factors of SCS slab on perforation velocity was quantitatively evaluated by variance analysis. The deviation between the predicted perforation velocity and the actual value is less than 12%, and the quantitative evaluation results of variance analysis show that the thickness of steel plate has a largest effect, followed by the distance of tie bar and the thickness of concrete, the yield strength of steel plate, the yield strength of tie bar and the diameter of tie bar have a smaller effect, and the concrete compressive strength has a smallest effect. The established model solves the prediction problem of perforation velocity from a new perspective with a good prediction effect, which can effectively evaluate the ability of SCS slab against perforation failure of missile impact, and the order of the factors is beneficial to the optimal design of SCS slab resisting perforation from missile impact.

, correspAuthors=Ying-chun LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Peng-fei HAN, Ying-chun LI, Jing-bo LIU, Fei WANG, Zhen-ping DONG), CN=ArticleExt(id=1149780500514038000, articleId=1149780473641132459, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=双钢板混凝土板抗弹体贯穿速度预测及因素评估, columnId=1156264150092342198, journalTitle=科学技术与工程, columnName=论文·力学, runingTitle=null, highlight=null, articleAbstract=

为预测弹体撞击双钢板混凝土板的贯穿速度及获得结构因素对贯穿速度的影响排序,基于量纲分析和人工神经网络建立了贯穿速度无量纲方程和预测模型,并采用正交试验法确定有限元计算工况,结合方差分析定量评价了7种板的结构因素对贯穿速度的影响程度。结果表明,贯穿速度预测模型的预测值与实际值的误差小于12%;钢板厚度影响显著,对拉钢筋间距和混凝土厚度影响较大,钢板屈服强度、对拉钢筋屈服强度、对拉钢筋直径影响较小,混凝土抗压强度影响最小。建立的贯穿速度预测模型预测效果良好,从新的角度解决了贯穿速度的预测问题,可有效评估双钢板混凝土板抗弹体贯穿的能力,结构因素影响排序有益于双钢板混凝土板抗弹体贯穿的优化设计。

, correspAuthors=李映春, authorNote=null, correspAuthorsNote=
* 李映春(1982—),男,汉族,河南商丘人,工程师。研究方向:防护工程设计。E-mail:
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韩鹏飞(1980—),男,汉族,山东青岛人,博士,高级工程师。研究方向:结构抗冲击与工程检测鉴定。E-mail:

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韩鹏飞(1980—),男,汉族,山东青岛人,博士,高级工程师。研究方向:结构抗冲击与工程检测鉴定。E-mail:

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韩鹏飞(1980—),男,汉族,山东青岛人,博士,高级工程师。研究方向:结构抗冲击与工程检测鉴定。E-mail:

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tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=图6, caption=贯穿速度有限元计算值和预测模型预测值对比, figureFileSmall=sOkX5GwRJ8Rv8gt3pAPt1w==, figureFileBig=R0POrEiEergvtdhA1s0MNA==, tableContent=null), ArticleFig(id=1218525103420261305, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 1, caption=

Orthogonal design table for perforation velocity of finite element calculation

, figureFileSmall=null, figureFileBig=null, tableContent=
试验数 钢板厚度/mm 钢板屈服
强度/MPa
混凝土
强度/MPa
混凝土
厚度/mm
对拉钢筋
直径/mm
对拉钢筋
间距/mm
对拉钢筋屈
服强度/mm
1 8 250 30 175 10 50 307
2 8 307 40 250 13 75 345
3 8 345 50 300 16 150 400
4 10 250 30 250 13 150 400
5 10 307 40 300 16 50 307
6 10 345 50 175 10 75 345
7 14 250 40 175 16 75 400
8 14 307 50 250 10 150 307
9 14 345 30 300 13 50 345
10 8 250 50 300 13 75 307
11 8 307 30 175 16 150 345
12 8 345 40 250 10 50 400
13 10 250 40 300 10 150 345
14 10 307 50 175 13 50 400
15 10 345 30 250 16 75 307
16 14 250 50 250 16 50 345
17 14 307 30 300 10 75 400
18 14 345 40 175 13 150 307
), ArticleFig(id=1218525103516730315, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表1, caption=

贯穿速度有限元计算工况正交试验设计表

, figureFileSmall=null, figureFileBig=null, tableContent=
试验数 钢板厚度/mm 钢板屈服
强度/MPa
混凝土
强度/MPa
混凝土
厚度/mm
对拉钢筋
直径/mm
对拉钢筋
间距/mm
对拉钢筋屈
服强度/mm
1 8 250 30 175 10 50 307
2 8 307 40 250 13 75 345
3 8 345 50 300 16 150 400
4 10 250 30 250 13 150 400
5 10 307 40 300 16 50 307
6 10 345 50 175 10 75 345
7 14 250 40 175 16 75 400
8 14 307 50 250 10 150 307
9 14 345 30 300 13 50 345
10 8 250 50 300 13 75 307
11 8 307 30 175 16 150 345
12 8 345 40 250 10 50 400
13 10 250 40 300 10 150 345
14 10 307 50 175 13 50 400
15 10 345 30 250 16 75 307
16 14 250 50 250 16 50 345
17 14 307 30 300 10 75 400
18 14 345 40 175 13 150 307
), ArticleFig(id=1218525103688696795, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 2, caption=

Parameters of MAT003 (steel)

, figureFileSmall=null, figureFileBig=null, tableContent=
参数 密度/
(kg·m-3)
屈服强度/
MPa
弹性模量/
MPa
切线模量/
MPa
泊松比 P Q 失效参数
FS
钢板 7.8×103 307 2.1×105 603 0.3 40 5 0.28
栓钉/对拉钢筋 7.8×103 345 2.1×105 504 0.3 40 5 0.3
弹体 7.8×103 250 2.1×105 502 0.3 40 5 0.3
), ArticleFig(id=1218525103852274673, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表2, caption=

MAT003(钢材)参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数 密度/
(kg·m-3)
屈服强度/
MPa
弹性模量/
MPa
切线模量/
MPa
泊松比 P Q 失效参数
FS
钢板 7.8×103 307 2.1×105 603 0.3 40 5 0.28
栓钉/对拉钢筋 7.8×103 345 2.1×105 504 0.3 40 5 0.3
弹体 7.8×103 250 2.1×105 502 0.3 40 5 0.3
), ArticleFig(id=1218525104028434437, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 3, caption=

Result comparison of test and finite element calculation

, figureFileSmall=null, figureFileBig=null, tableContent=
工况 混凝土厚度/
mm
钢板厚度/
mm
撞击速度/
(m·s-1)
破坏形态 剩余速度/(m·s-1)
有限元计算 试验 有限元计算 试验
SCS-175-6T 175 6 152.4 贯穿 贯穿 31.1 33.9
SCS-250-6T 250 6 147.7 鼓包 鼓包 0 0
), ArticleFig(id=1218525104179429395, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表3, caption=

有限元计算和试验结果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
工况 混凝土厚度/
mm
钢板厚度/
mm
撞击速度/
(m·s-1)
破坏形态 剩余速度/(m·s-1)
有限元计算 试验 有限元计算 试验
SCS-175-6T 175 6 152.4 贯穿 贯穿 31.1 33.9
SCS-250-6T 250 6 147.7 鼓包 鼓包 0 0
), ArticleFig(id=1218525104292675621, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 4, caption=

Finite element calculation results of perforation velocity

, figureFileSmall=null, figureFileBig=null, tableContent=
工况 贯穿速度/
(m·s-1)
工况 贯穿速度/
(m·s-1)
工况 贯穿速度/
(m·s-1)
1 136 7 167.5 13 157
2 151 8 185.5 14 167
3 147 9 207 15 174
4 155 10 153 16 198
5 186 11 144 17 181
6 160 12 161 18 175.9
), ArticleFig(id=1218525104384950319, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表4, caption=

贯穿速度有限元计算结果

, figureFileSmall=null, figureFileBig=null, tableContent=
工况 贯穿速度/
(m·s-1)
工况 贯穿速度/
(m·s-1)
工况 贯穿速度/
(m·s-1)
1 136 7 167.5 13 157
2 151 8 185.5 14 167
3 147 9 207 15 174
4 155 10 153 16 198
5 186 11 144 17 181
6 160 12 161 18 175.9
), ArticleFig(id=1218525104498196541, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 5, caption=

Value comparison of perforation velocity between finite element calculation and output of prediction model

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/% 序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/% 序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/%
1 135 144.66 7.16 14 165 154.33 -6.47 27 136 138.95 2.17
2 127 135.74 6.88 15 157 155.45 -0.99 28 151 151.08 0.05
3 170 172.91 1.71 16 169 168.27 -0.43 29 155 154.60 -0.26
4 147 147.18 0.13 17 177 174.77 -1.26 30 186 189.90 2.10
5 160 152.53 -4.67 18 150 149.88 -0.08 31 167.5 174.89 4.41
6 139 142.33 2.39 19 168 176.60 5.12 32 185.5 183.76 -0.94
7 199 188.94 -5.05 20 153 152.69 -0.20 33 144 143.44 -0.39
8 173 174.82 1.05 21 158 155.46 -1.61 34 161 161.19 0.12
9 178 178.25 0.14 22 160 163.82 2.38 35 167 160.52 -3.88
10 167 163.18 0.11 23 170 167.27 -0.44 36 174 174.69 0.40
11 153 152.80 -0.13 24 129 129.94 0.73 37 181 181.82 0.45
12 174 169.70 -2.47 25 159 158.22 -0.49 38 175.9 170.34 -3.16
13 162 169.44 4.59 26 146 154.12 5.56
), ArticleFig(id=1218525104665968715, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表5, caption=

贯穿速度有限元计算值和预测模型输出值对比

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序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/% 序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/% 序号 有限元计算
值/(m·s-1)
训练输出
值/(m·s-1)
误差/%
1 135 144.66 7.16 14 165 154.33 -6.47 27 136 138.95 2.17
2 127 135.74 6.88 15 157 155.45 -0.99 28 151 151.08 0.05
3 170 172.91 1.71 16 169 168.27 -0.43 29 155 154.60 -0.26
4 147 147.18 0.13 17 177 174.77 -1.26 30 186 189.90 2.10
5 160 152.53 -4.67 18 150 149.88 -0.08 31 167.5 174.89 4.41
6 139 142.33 2.39 19 168 176.60 5.12 32 185.5 183.76 -0.94
7 199 188.94 -5.05 20 153 152.69 -0.20 33 144 143.44 -0.39
8 173 174.82 1.05 21 158 155.46 -1.61 34 161 161.19 0.12
9 178 178.25 0.14 22 160 163.82 2.38 35 167 160.52 -3.88
10 167 163.18 0.11 23 170 167.27 -0.44 36 174 174.69 0.40
11 153 152.80 -0.13 24 129 129.94 0.73 37 181 181.82 0.45
12 174 169.70 -2.47 25 159 158.22 -0.49 38 175.9 170.34 -3.16
13 162 169.44 4.59 26 146 154.12 5.56
), ArticleFig(id=1218525104825352279, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 6, caption=

Value comparison of perforation velocity between finite element calculation and prediction of prediction model

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序号 有限元计
算值/(m·s-1)
预测值/
(m·s-1)
误差/% 序号 有限元计
算值/(m·s-1)
预测值/
(m·s-1)
误差/%
1 151 155.34 2.87 11 168 163.63 -1.43
2 152 159.51 4.94 12 174 159.38 -8.40
3 183 164.08 -10.34 13 187 164.62 -11.97
4 160 159.97 -0.02 14 147 133.10 -9.46
5 147 148.85 1.26 15 160 152.10 -4.94
6 176 174.92 -0.62 16 207 199.14 -3.80
7 138 145.97 5.77 17 153 156.87 2.53
8 184 172.22 -6.40 18 157 150.79 -3.95
9 199 186.81 -6.12 19 198 193.12 -2.46
10 159 159.61 0.38
), ArticleFig(id=1218525104963764326, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表6, caption=

贯穿速度有限元计算值和预测模型预测值对比

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序号 有限元计
算值/(m·s-1)
预测值/
(m·s-1)
误差/% 序号 有限元计
算值/(m·s-1)
预测值/
(m·s-1)
误差/%
1 151 155.34 2.87 11 168 163.63 -1.43
2 152 159.51 4.94 12 174 159.38 -8.40
3 183 164.08 -10.34 13 187 164.62 -11.97
4 160 159.97 -0.02 14 147 133.10 -9.46
5 147 148.85 1.26 15 160 152.10 -4.94
6 176 174.92 -0.62 16 207 199.14 -3.80
7 138 145.97 5.77 17 153 156.87 2.53
8 184 172.22 -6.40 18 157 150.79 -3.95
9 199 186.81 -6.12 19 198 193.12 -2.46
10 159 159.61 0.38
), ArticleFig(id=1218525105093787766, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=EN, label=Table 7, caption=

Variance analysis of finite element calculation results

, figureFileSmall=null, figureFileBig=null, tableContent=
因素 方差来源 偏差平方和 自由度 平均偏差平方和 统计量MSk/MSe 统计量临界值
因素1 钢板厚度 4 142.57 2 2 071.28 61.02 F0.01(2, 3)=30.81
F0.05(2, 3)=9.55
F0.1(2, 3)=5.46
因素2 钢板屈服强度 323.48 2 161.74 4.76
因素3 混凝土抗压强度 18.37 2 9.18 0.27
因素4 混凝土厚度 668.30 2 334.15 9.84
因素5 对拉钢筋直径 120.02 2 60.01 1.77
因素6 对拉钢筋间距 743.83 2 371.92 10.96
因素7 对拉钢筋屈服强度 141.30 2 70.65 2.08
误差e 101.83 3 33.94
), ArticleFig(id=1218525105265754252, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149780473641132459, language=CN, label=表7, caption=

有限元计算结果方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
因素 方差来源 偏差平方和 自由度 平均偏差平方和 统计量MSk/MSe 统计量临界值
因素1 钢板厚度 4 142.57 2 2 071.28 61.02 F0.01(2, 3)=30.81
F0.05(2, 3)=9.55
F0.1(2, 3)=5.46
因素2 钢板屈服强度 323.48 2 161.74 4.76
因素3 混凝土抗压强度 18.37 2 9.18 0.27
因素4 混凝土厚度 668.30 2 334.15 9.84
因素5 对拉钢筋直径 120.02 2 60.01 1.77
因素6 对拉钢筋间距 743.83 2 371.92 10.96
因素7 对拉钢筋屈服强度 141.30 2 70.65 2.08
误差e 101.83 3 33.94
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双钢板混凝土板抗弹体贯穿速度预测及因素评估
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韩鹏飞 1, 2 , 李映春 3, * , 刘晶波 4 , 王菲 5 , 董振平 2
科学技术与工程 | 论文·力学 2025,25(10): 3986-3995
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科学技术与工程 | 论文·力学 2025, 25(10): 3986-3995
双钢板混凝土板抗弹体贯穿速度预测及因素评估
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韩鹏飞1, 2 , 李映春3, * , 刘晶波4, 王菲5, 董振平2
作者信息
  • 1 西安建筑科大工程技术有限公司, 西安 710055
  • 2 西安建筑科技大学土木工程学院, 西安 710055
  • 3 军事科学院国防工程研究院, 北京 100036
  • 4 土木工程安全与耐久教育部重点实验室/清华大学土木工程系, 北京 100084
  • 5 陆军工程大学国防工程学院, 南京 210007
  • 韩鹏飞(1980—),男,汉族,山东青岛人,博士,高级工程师。研究方向:结构抗冲击与工程检测鉴定。E-mail:

通讯作者:

* 李映春(1982—),男,汉族,河南商丘人,工程师。研究方向:防护工程设计。E-mail:
Prediction and Factor Evaluation of Perforation Velocity of Steel-Concrete-Steel Slab against Missile Impact
Peng-fei HAN1, 2 , Ying-chun LI3, * , Jing-bo LIU4, Fei WANG5, Zhen-ping DONG2
Affiliations
  • 1 Engineering Technology Co.,Ltd., Xi'an University of Architecture and Technology, Xi'an 710055, China
  • 2 College of Civil Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
  • 3 Institute of Defense Engineering, Academy of Military Sciences, Chinese People's Liberation Army, Beijing 100036, China
  • 4 Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University, Beijing 100084, China
  • 5 College of Defense Engineering, Army Engineering University, Chinese People's Liberation Army, Nanjing 210007, China
出版时间: 2025-04-08 doi: 10.12404/j.issn.1671-1815.2402766
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为预测弹体撞击双钢板混凝土板的贯穿速度及获得结构因素对贯穿速度的影响排序,基于量纲分析和人工神经网络建立了贯穿速度无量纲方程和预测模型,并采用正交试验法确定有限元计算工况,结合方差分析定量评价了7种板的结构因素对贯穿速度的影响程度。结果表明,贯穿速度预测模型的预测值与实际值的误差小于12%;钢板厚度影响显著,对拉钢筋间距和混凝土厚度影响较大,钢板屈服强度、对拉钢筋屈服强度、对拉钢筋直径影响较小,混凝土抗压强度影响最小。建立的贯穿速度预测模型预测效果良好,从新的角度解决了贯穿速度的预测问题,可有效评估双钢板混凝土板抗弹体贯穿的能力,结构因素影响排序有益于双钢板混凝土板抗弹体贯穿的优化设计。

双钢板混凝土板  /  贯穿速度  /  预测  /  结构因素  /  影响排序

In order to predict perforation velocity of SCS (steel-concrete-steel) slab against missile impact and obtain influence sequence of structural factors of SCS slab on the perforation velocity, a dimensionless equation of the perforation velocity was established and a prediction model was obtained based on dimensional analysis and artificial neural network. Orthogonal experiment design was used to determine finite element calculation, and the influence degree of 7 factors of SCS slab on perforation velocity was quantitatively evaluated by variance analysis. The deviation between the predicted perforation velocity and the actual value is less than 12%, and the quantitative evaluation results of variance analysis show that the thickness of steel plate has a largest effect, followed by the distance of tie bar and the thickness of concrete, the yield strength of steel plate, the yield strength of tie bar and the diameter of tie bar have a smaller effect, and the concrete compressive strength has a smallest effect. The established model solves the prediction problem of perforation velocity from a new perspective with a good prediction effect, which can effectively evaluate the ability of SCS slab against perforation failure of missile impact, and the order of the factors is beneficial to the optimal design of SCS slab resisting perforation from missile impact.

steel-concrete-steel slab  /  perforation velocity  /  prediction  /  structure factor  /  influence sequence
韩鹏飞, 李映春, 刘晶波, 王菲, 董振平. 双钢板混凝土板抗弹体贯穿速度预测及因素评估. 科学技术与工程, 2025 , 25 (10) : 3986 -3995 . DOI: 10.12404/j.issn.1671-1815.2402766
Peng-fei HAN, Ying-chun LI, Jing-bo LIU, Fei WANG, Zhen-ping DONG. Prediction and Factor Evaluation of Perforation Velocity of Steel-Concrete-Steel Slab against Missile Impact[J]. Science Technology and Engineering, 2025 , 25 (10) : 3986 -3995 . DOI: 10.12404/j.issn.1671-1815.2402766
双钢板混凝土(steel-concrete-steel,SCS)板作为一种新型组合结构,通常由两块外包钢板、混凝土及位于钢混组合界面的剪力连接件(栓钉或对拉钢筋等)组成。该结构表现出良好的延性、密闭性、承载力、抗冲击与抗爆性能、施工便捷等特点[1],在核电厂房、高层建筑、储存罐体、沉箱隧道、近海工程设施、防护工程结构、极地工程防冰墙等工程结构中得到了广泛应用[2-5]
目前,SCS板已用于中国第三代核电站屏蔽厂房中[6-7],以防止内部钢制安全壳和反应堆冷却系统受到飞射物的撞击破坏;SCS板用于防护工程结构中,以抵抗弹体的贯穿破坏或爆炸效应。因此飞射物或弹体(下文统称弹体)对SCS板的贯穿破坏是一项重要的研究内容,已成为中外的研究热点,并受到越来越广泛的关注。不过SCS结构相比于钢筋混凝土结构出现的比较晚,带对拉钢筋的SCS板抗弹体撞击贯穿问题的研究相对少见。
由于军用及核工业等部门的需求,弹体对钢筋混凝土板的贯穿问题得到了广泛研究,留下了宝贵的试验数据和相关经验公式,中外许多学者[8-12]也对这些不同时期的经验公式进行过比较详尽的讨论比较,并指出了这些经验公式的使用条件和优缺点。Li等[13-14]和Chen等[15]基于空腔膨胀理论给出了刚性弹体贯穿素混凝土的最小混凝土厚度和贯穿混凝土的能量计算公式,给出公式的计算结果与试验结果吻合得较好,以及给出了刚性弹体贯穿钢筋混凝土的计算方法。张爽[16]和武海军等[17]获得了钢筋对弹体的阻力模型,采用微分面力法,建立刚性弹体贯穿有限厚钢筋混凝土靶的弹道计算模型,并验证了模型的准确性。宋春明等[18]和王冰彬[19]将弹体贯穿钢筋混凝土安全壳分为几个阶段来计算,给出的计算结果与试验结果匹配良好。
Bruhl等[20]给出了单钢板混凝土抗刚性弹体贯穿的计算方法,以此计算方法来代替SCS板的抗贯穿计算方法,没有考虑对拉钢筋的作用,也没有考虑前钢板的作用。Han等[21-22]分析了弹体撞击SCS板的贯穿机制,建立了基于能量方法的抗贯穿计算公式,公式计算结果与试验结果,以及数十个有限元工况分析结果匹配良好,该计算公式能有效评估带对拉钢筋SCS板的贯穿破坏;并指出了运用解耦方法研究飞机撞击屏蔽厂房的关键问题是:获取正确撞击力时程曲线和确定合理的撞击力加载面积,两者缺一不可。程毅等[23]基于动能守恒定律,运用钢板单独抗贯穿经验公式将钢板转换为等效混凝土,并利用混凝土抗贯穿经验公式得到3个不同的剩余速度预测公式,没有考虑对拉钢筋的作用,得出的剩余速度预测公式依赖于所使用经验公式的准确性。王武等[24]基于能量守恒原理,提出了双钢板混凝土遮弹层防贯穿设计六步法,给出了弹体临界贯穿速度和弹体余速计算公式,但是计算过程比较复杂,SCS板的整体耗能大致分为3个部分的耗能,忽略了SCS板的整体相互作用,而且每部分的耗能需要在以往研究成果中选取合理的计算公式来计算。Xu 等[25]基于能量守恒原理,将SCS板耗散的能量分为前、后钢板和钢筋混凝土分别耗散的能量3部分,钢筋混凝土耗散的能量依据4种现有的经验公式来计算,并根据4炮次贯穿试验数据修正了剩余速度的计算公式,不过剩余速度的计算公式没有考虑对拉钢筋的作用,依赖于经验公式的准确程度,而且修正公式的试验数据过少。Kim等[26-27]进行了缩比SCS板抗弹体贯穿的试验和有限元计算,目的是验证Bruhl等[20]给出的抗贯穿计算方法的有效性和SCS板的破坏形式;Bruhl等[20]的计算方法给出的贯穿速度计算结果偏于保守,保守率达到6%~32%,而且指出修正的美国国防研究委员会(National Defence Research Committee, NDRC)方法在某些条件下计算结果并不理想,与试验结果偏差较大。
目前,对SCS板抗弹体撞击贯穿速度的研究途径主要有:撞击试验、理论分析和数值计算。本文研究梳理钢筋混凝土板抗弹体贯穿的研究成果,以期受到启发而利于本文研究内容的开展,通过梳理可以发现:由于撞击试验成本高、实施难度较大,撞击试验数据较少,因此通过撞击试验获得SCS板抗弹体贯穿速度的计算公式相对困难;SCS板抗弹体贯穿的复杂特性,导致理论计算很难给出贯穿速度的解析解,而且计算过程复杂,利用经验公式又需要考虑经验公式的限制条件,准确度有待调高;而数值计算主要运用数值计算软件来完成,经试验数据验证过的数值计算模型可得到不同工况下的贯穿速度,利用数学计算软件MATLAB预测SCS板的贯穿速度比较少见,可直接用于工程中达到便捷、高效、批量化计算的抗弹体贯穿实用计算模型更为缺乏;从SCS板结构方面来定量分析评价不同因素对SCS板贯穿速度的影响程度大小,且给出影响因素排序,鲜见相关文献报道。
因此,现建立SCS板的贯穿速度预测模型,以实现便捷、高效、准确、批量化,并给出SCS板的结构因素对贯穿速度影响程度的大小排序,以利于SCS板结构抗弹体贯穿的优化设计。
有些现象或问题的研究,可以借助或采用现成的物理和数学模型和方程;然而,更多的复杂现象或问题,无法利用现成的数学方程来表述,这时,更有需要采用量纲分析的方法来分析问题[28]。为了建立SCS板抗弹体的贯穿速度预测模型,就需要分析SCS板抗弹体贯穿的影响因素,其主要存在两大方面:弹体方面和SCS板方面,并进行量纲分析。
(1)弹体方面:弹体形状系数ψ,直径d,长度l,弹性模量Ep,剪切模量Gp,密度ρp,屈服强度σp,泊松比γp,命中角β,旋转角速度ω
(2)SCS板方面:钢板厚度Hs,弹性模量Es,剪切模量Gs,密度ρs,屈服强度σs,泊松比γs;混凝土厚度Hc,弹性模量Ec,剪切模量Gc,密度ρc、抗压强度σc,泊松比γc;对拉钢筋间距st,对拉钢筋直径dt,弹性模量Et,剪切模量Gt,密度ρt,屈服强度σt,泊松比γt
从上面的诸多因素中可以看出,要预测弹体对SCS板的贯穿速度Vp,就需要获得Vp与上述因素的某种函数关系f
V p = f ( ψ , d , l , E p , G p , σ p , ρ p , H s , E s , G s , σ s , ρ s , H c , E c , G c , σ c , ρ c , s t , d t , E t , G t , σ t , ρ t , γ p , γ s , γ c , γ t , β , ω )
由式(1)可知影响弹体贯穿速度的变量为29个。首先由于本文拟分析的弹体为平头刚性弹体,那么弹体形状系数ψ、弹性模量Ep、剪切模量Gp、屈服强度σp和泊松比γp可以在式(1)中去掉;其次,弹体撞击SCS板时,仅考虑垂直撞击,且不考虑旋转角速度,所以这两个因素变量也可以在式(1)中去掉;最后,钢板、对拉钢筋、混凝土在得知弹性模量、泊松比的情况下,其剪切模量可通过近似公式进行估算,所以三者的剪切模量在式(1)中也可去掉。所以式(1)简化为
V p = f ( d , l , ρ p , H s , E s , σ s , ρ s , H c , E c , σ c , ρ c , s t , d t , E t , σ t , ρ t , γ s , γ c , γ t )
由式(2)可知,影响弹体贯穿速度的因素变量变为19个。选取物理量lρcσcγc 4个具有独立量纲的物理量作为基本量,其他物理量都可以用这些基本量变化成无量纲的量,于是可得到无量纲的函数关系,即
V p σ c ρ c 1 / 2 = f ( l d , l H s , ρ p ρ c , E s σ c , σ s σ c , ρ s ρ c , l H c , E c σ c , l s t , l d t , E t σ c , σ t σ c , ρ t ρ c , γ s γ c , γ t γ c )
人工神经网络,是一种通过对大脑神经网络记忆、处理信息而建立起来的智能算法[29-30]。它具有强大的非线性处理能力,大规模的并行处理和分布式的信息存储能力,良好的自适应性、自组织性及很强的学习、联想、容错及抗干扰能力,可为那些难于建立准确计算公式的问题提供解决方法。目前人工神经网络中应用较多的是BP网络模型,已应用于多个学科领域,对不确定性模式识别具有独到之处。根据文献[31]可知,BP网络模型是一种多层前馈型神经网络,由一个输入层、一个输出层及一个或多个隐层组成,每一层可以有若干个节点,不同层之间的联系方式是全连接,相同层的神经元之间是不发生任何连接的。BP网络模型通过不断调整层与层之间的连接权值使目标函数最小化,如果输出响应与期望输出模式的误差不满足要求,则误差值沿连接通路逐层反向传送并修正各层连接权值,当各个训练模式都满足要求时,则学习训练结束。本文研究拟采用BP网络模型来预测弹体撞击SCS板的贯穿速度。
对于训练样本,可以来自相关试验,也可以来自数值计算分析。SCS板抗弹体撞击的有关试验在文献报道中比较少见,Kim等[32]对SCS板遭遇钝头弹体撞击的动态毁伤特性进行了试验研究,遗憾的是试验次数仅有几次,而且试验中SCS板未设置对拉钢筋。Han等[21]对Kim等[32]的试验进行了有限元模拟计算,有限元计算结果和试验结果匹配程度较高,验证了有限元模型和参数设置的合理性,并给出了数十个工况的贯穿速度。本文研究从Han等[21]的研究中选取39个工况作为本文的部分训练样本,并利用有限元模拟计算增加训练样本数量。本文的有限元计算工况,主要是考虑变化SCS板中的钢板厚度、钢板屈服强度、混凝土抗压强度、混凝土厚度、对拉钢筋直径、对拉钢筋间距和对拉钢筋屈服强度这7种因素,每种因素从常用材料和常规设计出发变化3次。为了节约有限元模拟计算次数,又能科学分析本文所研究的问题,采用正交试验设计法来获取有限元计算工况。正交试验是使用正交表来分析多因素试验的一种高效率、快速、经济的研究方法,通过探讨典型组合案例来对整个试验的情况进行探究。本文研究采用7因素3水平的正交设计表格,得到了18种有限元计算工况,如表1所示,则可代替2 187次有限元计算工况。由本文的18个有限元计算工况与Han等[21]研究中的39个工况组成本文基于人工神经网络所建贯穿速度预测模型的样本。
弹体撞击SCS板的试验[32]目的是研究SCS板遭遇弹体撞击的动态毁伤特性,弹体头部为拱顶头部,弹体规格如图1所示。弹体质量约为40 kg,试验中弹体的初始撞击速度约为150 m/s,SCS板靶体大小为2 000 mm×2 000 mm,靶体厚度分别为175 mm和250 mm,钢板的厚度约为6 mm,靶体试验模型中没有对拉钢筋,栓钉的直径为13 mm,长度为80 mm,栓钉间距为150 mm。
对本次试验用有限元软件LS-DYNA建模,其参数设置如下[21]:混凝土的本构模型采用MAT072R3,单元失效采用MAT_ADD_EROSION 的最大应变控制,混凝土密度为2.37´103 kg/m3,抗压强度为50.075 MPa,泊松比为0.19;钢材模型采用MAT003,应变率模型采用Cowper-Symonds模型,如式(4)所示;混凝土采用实体单元,钢板和栓钉分别采用壳单元和梁单元,栓钉和混凝土共节点,弹体与SCS板的接触采用*CONTACT_AUTOMATIC_SINGLE_SURFACE;板四周在撞击方向上施加约束。钢材模型参数如表2所示。
σ y d = σ y 1 + ε · Q 1 / P
式(4)中:σyd为动态屈服强度;σy为屈服强度; ε ·为应变率;PQ为与材料相关的常数。
对于SCS-175-6T板的毁伤特点,图2进行了数值计算结果和试验结果的对比。弹体的撞击速度为152.4 m/s,由图2不能难看出试验中SCS板的破坏形态为贯穿,有限元模拟结果与试验结果一致,前后钢板均被破坏,并出现孔洞。对于SCS-250-6T板,有限元计算结果和试验结果如图3所示,弹体的撞击速度为147.7 m/s,由图3可以看出试验的破坏形态为鼓包,有限元模拟结果与试验结果一致。前钢板完全被穿透,但是后钢板并没有被贯穿,弹体完全侵入SCS板中,在撞击中心位置有较大的鼓包形成。
对于弹体剩余速度和破坏形态,有限元计算结果和试验结果如表3所示。SCS-175-6T试验中弹体贯穿板后的剩余速度为33.9 m/s,而有限元模拟结果为31.1 m/s,两者比较接近;SCS-250-6T试验中剩余速度有限元计算结果和试验结果均为0。如图2图3表3所示,在这两次撞击试验中,通过有限元计算所得到的毁伤形式、剩余速度与试验结果符合得较好。通过对比分析,本文的有限元模型和参数设置合理性得到了验证,可用于下文多种工况的有限元模拟计算。
在有限元计算过程中,要恰好得到SCS板的贯穿速度,既能贯穿,又使得弹体剩余速度恰好为0,需要繁冗的试算工作,为了减少试算工作,本文研究中遵循的原则是:贯穿速度的误差不大于1 m/s。按照表1所示的18个工况进行有限元计算,弹体为刚性平头弹,直径为150 mm,质量约为70 kg,弹体垂直撞击SCS板。通过有限元计算分析,弹体撞击SCS板的贯穿速度如表4所示。
根据Han等[21]的39个工况和本文的18个工况,可以获得57组数据,经过式(3)的量纲分析,变化成无量纲输入参数,将其中的38组数据作为贯穿速度预测模型的训练样本,用于对该模型进行训练;剩余的19组数据作为贯穿速度预测模型的预测样本,输入训练好的预测模型,用于比较预测模型贯穿速度输出值与有限元计算结果(作为实际值)的对比,从而可评价所建预测模型的预测效果。由式(3)可以看出,影响贯穿速度的无量纲变量为15个,可通过训练样本来训练这15个无量纲变量组成的预测模型。因此输入节点为15个,运用MATLAB编程,并设计隐层为2层,输入训练样本,经过不断调整和试算,确定隐层第1层节点数为20个,隐层第二层节点数为9个,传递函数依次为tansig、tansig、purelin,输出函数为trainscg,训练计算过程如图4所示。
当建立的预测模型训练好后,将训练样本再次输入到模型中,计算模型的输出值,并与有限元计算值比较,比较结果如图5表5所示;将预测样本输入到训练好的模型中,计算模型的预测值,并与有限元计算值比较,比较结果如图6表6所示。由表5可以看出,训练输出值与有限元计算值相对误差均控制在10%内。由表6可以看出,预测值与有限元计算值进行对比,仅有2组数据相对误差超过10%,分别达到了-10.34%和-11.97%,其余数据相对误差均在10%以内。从结果分析可以看出,模型对贯穿速度的预测取得了较为满意的结果,为解决SCS板抗弹体贯穿速度的预测问题提供了一种新的方法,利用训练好的模型,可以发挥人工神经网络的优点,能便捷、高效、批量化地给出贯穿速度的预测结果。
为了得出各因素对贯穿速度影响程度的大小排序,拟依照数理统计原理,采用方差分析法对18个有限元工况的计算结果进行分析。方差分析可以研究不同因素的影响程度,通过确定总变异中不同因素的贡献程度实现影响力分析,方差分析主要通过F检验分析不同因素变异对总变异贡献的大小,步骤具体如下。
(1)计算总偏差的平方和ST
S T = k = 1 n ( x k - x - ) 2 = k = 1 n x k 2 - 1 n k = 1 n x k 2
式(5)中: x -为样本的总平均值;n为试验的总次数;xk为第k次试验结果。
总偏差平方和ST的数值表示试验结果的总体差异,其得到的数值越大,说明试验的差异越大。
(2)计算各因素偏差的平方和,以计算因素1的偏差的平方和S1为例说明,可看作单因素试验,则有
S 1 = 1 a i = 1 n a ( j = 1 a x i j ) 2 - 1 n ( i = 1 n a j = 1 a x i j ) 2 = 1 a i = 1 n a ( K i ) 2 - 1 n ( k = 1 n x k ) 2
式(6)中:xij为因素1的第i个水平的第j个试验的结果;na为因素1的水平数;a为每个水平的试验数;Ki为因素1的第i个水平a次试验结果的总和;S1为因素1对试验结果的影响差异。其他各因素的偏差平方和也可以用此方法得到。
(3)计算试验误差的偏差平方和Se,不考虑交互因素的作用,则有
S e = S T - k = 1 7 S k
式(7)中:Sk为第k个因素偏差的平方和,对于本文的正交试验案例共有7个因素。
(4)计算自由度,试验总自由度f=n-1;各因素的自由度,以因素1为例, f1=na-1。
(5)计算平均偏差平方和,则有
M S k = S k f k
式(8)中:MSk为第k个因素的平均偏差平方和;fk为第k个因素的自由度。
(6)对因素进行显著性检验,以因素1为例,取统计量F,即
F = M S 1 M S e ~ F ( n a - 1 , f e )
式(9)中:fe为误差自由度。
对给定的α,查出Fα(na-1, fe)的值,可与式(9)计算所得的F值进行比较。
根据式(6)计算每种因素的偏差平方和,并可根据式(8)计算得每种因素的平均偏差平方和,根据式(5)、式(7)和式(8)计算给出误差偏差平方和、平均误差偏差平方和,然后根据式(9)给出每种因素的统计量,从而查表进行显著性检验,有限元计算结果的方差分析结果如表7所示。通过F检验,7种因素的显著性检验统计量(MSk/MSe)大小排序为:因素1>因素6>因素4>因素2>因素7>因素5>因素3,根据上述方差的分析结果可知,各因素对贯穿速度的影响程度大小排序为钢板厚度>对拉钢筋间距>混凝土厚度>钢板屈服强度>对拉钢筋屈服强度>对拉钢筋直径>混凝土抗压强度。钢板厚度的统计量最大,达到61.02,对拉钢筋间距和混凝土厚度次之,两者的统计量大小较为接近,对拉钢筋屈服强度和对拉钢筋直径统计量大小较为接近,混凝土抗压强度统计量最小,仅为0.27。对于α=0.05,F1=61.02>F0.05(2,3),F6=10.96>F0.05(2,3),F4=9.84>F0.05(2,3),说明钢板厚度对贯穿速度的影响显著,对拉钢筋间距和混凝土厚度对贯穿速度的影响较为显著。
为了给出SCS板抗弹体撞击贯穿速度的预测方法,通过量纲分析给出了贯穿速度与诸多因素的无量纲函数关系,并基于人工神经网络,通过设计和编程,建立了贯穿速度预测模型。通过预测模型的训练和预测验证,对于贯穿速度,预测样本19组数据中误差绝对值有两个是10.34%和11.97%,其余在10%以内;训练样本38组数据中误差绝对值在10%以内。这说明本文建立的贯穿速度预测模型给出的计算结果是合理可信的,从新的角度解决了SCS板抗弹体贯穿速度的预测问题,能有效评估SCS板的贯穿破坏和进行相关工程设计。
影响SCS板贯穿速度的因素有很多,本文从SCS板的结构方面进行研究,有益于SCS板抗弹体贯穿的优化设计,主要从7个因素:钢板厚度、钢板屈服强度、混凝土厚度、混凝土抗压强度、对拉钢筋间距、对拉钢筋直径、对拉钢筋屈服强度出发,评价了这些因素对贯穿速度的影响程度。通过正交试验方法,确定了7因素3水平的正交试验方案,获得了18种有限元计算工况。根据18种工况的有限元计算结果,结合方差分析,定量评价了7种因素对贯穿速度的影响程度,钢板厚度影响显著,对拉钢筋间距和混凝土厚度影响较大,钢板屈服强度、对拉钢筋屈服强度、对拉钢筋直径影响较小,混凝土抗压强度影响最小,影响程度大小顺序依次是:钢板厚度>对拉钢筋间距>混凝土厚度>钢板屈服强度>对拉钢筋屈服强度>对拉钢筋直径>混凝土抗压强度。
在后续的研究中,首先SCS板抗弹体贯穿速度的人工神经网络预测模型可进一步优化,选取不同的网络模型或者算法,获取更加优化的计算模型,使得模型计算结果与实际结果的误差进一步缩小;其次,可对弹体方面的影响因素进行影响程度大小排序研究,也可从弹体和SCS板的两方面因素进行综合排序;最后,本文研究中探讨的贯穿速度属于较低的速度范围,变化SCS板的规格,对于更高的贯穿速度,采用何种方法合理预测,以及探讨影响因素排序,也是后续值得研究的问题。
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2025年第25卷第10期
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doi: 10.12404/j.issn.1671-1815.2402766
  • 接收时间:2024-04-16
  • 首发时间:2025-07-09
  • 出版时间:2025-04-08
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  • 收稿日期:2024-04-16
  • 修回日期:2024-12-30
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    1 西安建筑科大工程技术有限公司, 西安 710055
    2 西安建筑科技大学土木工程学院, 西安 710055
    3 军事科学院国防工程研究院, 北京 100036
    4 土木工程安全与耐久教育部重点实验室/清华大学土木工程系, 北京 100084
    5 陆军工程大学国防工程学院, 南京 210007

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* 李映春(1982—),男,汉族,河南商丘人,工程师。研究方向:防护工程设计。E-mail:
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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
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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