Article(id=1244316351569969300, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, articleNumber=null, orderNo=null, doi=10.16285/j.rsm.2024.1585, pmid=null, cstr=32223.14.j.rsm.2024.1585, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734969600000, receivedDateStr=2024-12-24, revisedDate=null, revisedDateStr=null, acceptedDate=1749139200000, acceptedDateStr=2025-06-06, onlineDate=1774597736494, onlineDateStr=2026-03-27, pubDate=1763049600000, pubDateStr=2025-11-14, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774597736494, onlineIssueDateStr=2026-03-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774597736494, creator=13701087609, updateTime=1774597736494, updator=13701087609, issue=Issue{id=1244316342938087728, tenantId=1146029695717560320, journalId=1244215477623373855, year='2025', volume='46', issue='11', pageStart='3329', pageEnd='3672', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1774597734436, creator=13701087609, updateTime=1774597825220, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1244316723801862468, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1244316723806056773, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3661, endPage=3672, ext={EN=ArticleExt(id=1244316351817433245, articleId=1244316351569969300, tenantId=1146029695717560320, journalId=1244215477623373855, language=EN, title=Investigation into transmission coefficient of calcareous sand: waveform coupling effects and gradient boosting prediction method, columnId=1244316348088693118, journalTitle=Rock and Soil Mechanics, columnName=Numerical Analysis, runingTitle=null, highlight=null, articleAbstract=

The variation in characteristic values of stress waves before and after passing through a material serves as a critical basis for evaluating its wave attenuation capacity. This can be characterized by the ratio of transmitted wave amplitude to the initial incident wave amplitude (i.e., transmission coefficient) in SHPB tests. However, due to the close correlation between the transmission coefficient and waveform parameters, it remains challenging to establish a quantitative characterization method for the transmission coefficient. Therefore, this study focuses on porous, irregular, and fragile calcareous sand as the research object. By combining physical experiments with numerical simulations, we investigate the influence of pulse width, platform duration, rising edge rate, falling edge rate, peak stress, and the central axis of symmetry on the transmission coefficient of calcareous sand. It is found that the transmission coefficient responds significantly to the coupling effects of the pulse width and the central axis of symmetry of the stress wave, the coupling effects of the platform section duration and the rising and falling edge rates, the coupling effects of the pulse width and the peak stress, as well as the coupling effects of the falling edge rate and the pulse width. Conversely, the response to the coupled effects of peak stress, rising edge rate, and falling edge rate is not pronounced. Owing to the difficulty in completely decoupling these waveform parameters, a prediction method is proposed for the transmission coefficient based on the gradient boosting algorithm, which effectively addresses multi-factor coupling issues. When the number of training samples reaches 91, the prediction accuracy exceeds 96%, which can effectively establish the mapping relationship between waveform parameters and transmission coefficients, providing a reference basis for the load design and calculation of protective engineering structures.

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应力波穿过材料前后的特征值变化是判断材料波衰减能力的重要依据,可通过霍普金森杆(split Hopkinson bar,简称SHPB)试验中透射波幅值与初始入射波幅值的比值(即透射系数)进行表征。然而,因透射系数与波形参数密切相关,目前还难以建立透射系数的定量表征方法。以多孔、不规则、易破碎的钙质砂为研究对象,通过物理试验和数值模拟相结合的方法,探究了脉宽、平台段时程、上升沿速率、下降沿速率、应力峰值以及中心对称轴对钙质砂透射系数的影响,发现透射系数随着应力波的脉宽和中心对称轴耦合作用、平台段时程和上升及下降沿速率耦合作用、脉宽和峰值应力耦合作用以及下降沿速率和脉宽耦合作用的响应明显,而随峰值应力、上升沿与下降沿速率三者耦合作用的响应不明显。针对波形参数难以完全解耦,提出了基于梯度提升算法的透射系数预测方法,可有效表征多因素耦合问题。当训练样本达到91个时,预测精度达到96%以上,可以很好地建立波形参数与透射系数的映射关系,为防护工程结构荷载设计计算提供参考依据。

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吕亚茹,女,1987年生,博士,教授,主要从事岩土率相关理论及工程应用研究。E-mail:
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邵国建,男,1962年生,博士,教授,主要从事岩土率相关理论及工程应用研究工作。E-mail:

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邵国建,男,1962年生,博士,教授,主要从事岩土率相关理论及工程应用研究工作。E-mail:

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邵国建,男,1962年生,博士,教授,主要从事岩土率相关理论及工程应用研究工作。E-mail:

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boosting algorithm, figureFileSmall=0l3us8pIcgQ0JonglHR2/Q==, figureFileBig=tQgkQxwd4S3Qvy1pLMjXOA==, tableContent=null), ArticleFig(id=1244316374915465351, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=图14, caption=梯度提升算法所得透射系数预测值与真实值对比, figureFileSmall=0l3us8pIcgQ0JonglHR2/Q==, figureFileBig=tQgkQxwd4S3Qvy1pLMjXOA==, tableContent=null), ArticleFig(id=1244316375016128656, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 1, caption=

Basic parameters of calcareous sand specimens

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Gs D/mm D50/mm Cu Cc emax emin Dr/%
2.810.18~1.180.551.860.951.3891.04990
), ArticleFig(id=1244316375141957782, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表1, caption=

钙质砂试样基本参数

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Gs D/mm D50/mm Cu Cc emax emin Dr/%
2.810.18~1.180.551.860.951.3891.04990
), ArticleFig(id=1244316375234232478, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 2, caption=

Summary of SHPB tests

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号试样长度/mm冲击速度/(m·s−1入射波峰值/MPa透射波峰值/MPa透射系数
#011812.3499.7520.390.204
#021812.3898.7216.590.168
#031812.61100.2014.860.148
#041812.2396.3917.210.179
#053712.24106.7511.420.107
#063712.37104.098.460.082
#073712.26102.229.660.095
#083712.0998.1610.610.108
#093712.61103.3211.530.112
#105512.38105.887.740.073
#115512.53109.277.490.069
#125512.2899.018.130.082
#135512.5894.298.120.086
#147412.35108.697.400.068
#157412.22105.317.090.067
#167412.30102.137.110.069
#177412.6794.656.540.069
#1811112.29109.295.110.047
#1911112.14104.214.470.043
#2011112.07105.325.140.049
#2111112.6999.534.730.048
), ArticleFig(id=1244316375364255912, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表2, caption=

试验工况表

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号试样长度/mm冲击速度/(m·s−1入射波峰值/MPa透射波峰值/MPa透射系数
#011812.3499.7520.390.204
#021812.3898.7216.590.168
#031812.61100.2014.860.148
#041812.2396.3917.210.179
#053712.24106.7511.420.107
#063712.37104.098.460.082
#073712.26102.229.660.095
#083712.0998.1610.610.108
#093712.61103.3211.530.112
#105512.38105.887.740.073
#115512.53109.277.490.069
#125512.2899.018.130.082
#135512.5894.298.120.086
#147412.35108.697.400.068
#157412.22105.317.090.067
#167412.30102.137.110.069
#177412.6794.656.540.069
#1811112.29109.295.110.047
#1911112.14104.214.470.043
#2011112.07105.325.140.049
#2111112.6999.534.730.048
), ArticleFig(id=1244316375464919218, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 3, caption=

Numerical simulation operating conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
A组:应力峰值与上升沿及下降沿速率的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#A-0110005050185018、23、28、33、
#A-0210005050485038、54、72、93、111、130、144
#A-03100050507850
B组:平台段时程与上升沿及下降沿速率的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#B-0120001001007810038、54、72、93、111、130、144
#B-02200100505078100
#B-03200150252578100
C组:脉宽及中心对称轴的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#C-0110005050785038、54、72、93、111、130、144
#C-02150075757875
#C-03200010010078100
D组:应力峰值及脉宽的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#D-014602323182338、54、72、93、111、130、144
#D-02124062624862
#D-03200010010078100
E组:入射应力波的下降沿速率及脉宽的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#E-011000505078 38、54、72、93、111、130、144
#E-0215005010078
#E-0320005015078
), ArticleFig(id=1244316375620108474, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表3, caption=

模拟工况

, figureFileSmall=null, figureFileBig=null, tableContent=
A组:应力峰值与上升沿及下降沿速率的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#A-0110005050185018、23、28、33、
#A-0210005050485038、54、72、93、111、130、144
#A-03100050507850
B组:平台段时程与上升沿及下降沿速率的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#B-0120001001007810038、54、72、93、111、130、144
#B-02200100505078100
#B-03200150252578100
C组:脉宽及中心对称轴的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#C-0110005050785038、54、72、93、111、130、144
#C-02150075757875
#C-03200010010078100
D组:应力峰值及脉宽的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#D-014602323182338、54、72、93、111、130、144
#D-02124062624862
#D-03200010010078100
E组:入射应力波的下降沿速率及脉宽的影响
编号脉宽/µs平台段时程/µs上升沿脉宽/µs下降沿脉宽/µs应力峰值/MPa中心对称轴位置对应的时程/µs试样长度/mm
#E-011000505078 38、54、72、93、111、130、144
#E-0215005010078
#E-0320005015078
), ArticleFig(id=1244316375741743297, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 4, caption=

Detailed settings of numerical model

, figureFileSmall=null, figureFileBig=null, tableContent=
模型部分尺寸(D×L)/mm单元类型类型单元数/个
入射杆37×2 000Soild16438 500
透射杆37×2 000Soild16438 500
试样37×18Soild1645 868
侧限钢套筒37×94(δ=10)Soild164780
), ArticleFig(id=1244316375871766727, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表4, caption=

数值模拟的计算模型

, figureFileSmall=null, figureFileBig=null, tableContent=
模型部分尺寸(D×L)/mm单元类型类型单元数/个
入射杆37×2 000Soild16438 500
透射杆37×2 000Soild16438 500
试样37×18Soild1645 868
侧限钢套筒37×94(δ=10)Soild164780
), ArticleFig(id=1244316375989207248, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 5, caption=

Material parameters of the numerical model for calcareous sand

, figureFileSmall=null, figureFileBig=null, tableContent=
ρ/(kg·m−3 G/MPa Ku/MPa a0/kPa a1/kPa a2
1 178107.7647.384.7716.230.777
), ArticleFig(id=1244316376081481942, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表5, caption=

钙质砂数值模型材料参数

, figureFileSmall=null, figureFileBig=null, tableContent=
ρ/(kg·m−3 G/MPa Ku/MPa a0/kPa a1/kPa a2
1 178107.7647.384.7716.230.777
), ArticleFig(id=1244316376207311071, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=EN, label=Table 6, caption=

Relevant parameters of fitted curves

, figureFileSmall=null, figureFileBig=null, tableContent=
组数工况 A t y R2
A组#A-010.29536.3590.0400.999
#A-020.29324.4400.0440.979
#A-030.64516.7340.0430.995
B组#B-011.17928.5410.0760.999
#B-020.85154.5430.0480.997
#B-030.894120.534−0.1120.983
C组#C-010.35227.2690.0410.993
#C-020.88925.7300.0660.999
#C-031.17928.5410.0760.999
D组#D-010.15840.4080.0190.998
#D-020.31047.0990.0660.996
#D-031.17928.5410.0760.999
E组#E-010.894120.534−0.1120.983
#E-020.87225.1680.0690.997
#E-030.35227.2690.0410.992
), ArticleFig(id=1244316376379277544, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316351569969300, language=CN, label=表6, caption=

拟合曲线相关参数

, figureFileSmall=null, figureFileBig=null, tableContent=
组数工况 A t y R2
A组#A-010.29536.3590.0400.999
#A-020.29324.4400.0440.979
#A-030.64516.7340.0430.995
B组#B-011.17928.5410.0760.999
#B-020.85154.5430.0480.997
#B-030.894120.534−0.1120.983
C组#C-010.35227.2690.0410.993
#C-020.88925.7300.0660.999
#C-031.17928.5410.0760.999
D组#D-010.15840.4080.0190.998
#D-020.31047.0990.0660.996
#D-031.17928.5410.0760.999
E组#E-010.894120.534−0.1120.983
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钙质砂透射系数探究:波形耦合作用及梯度提升预测方法
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邵国建 , 毛泽辉 , 苏宇宸 , 焦泓程 , 吕亚茹
岩土力学 | 数值分析 2025,46(11): 3661-3672
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岩土力学 | 数值分析 2025, 46(11): 3661-3672
钙质砂透射系数探究:波形耦合作用及梯度提升预测方法
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邵国建 , 毛泽辉, 苏宇宸, 焦泓程, 吕亚茹
作者信息
  • 河海大学 力学与工程科学学院,江苏 南京 211100
  • 邵国建,男,1962年生,博士,教授,主要从事岩土率相关理论及工程应用研究工作。E-mail:

通讯作者:

吕亚茹,女,1987年生,博士,教授,主要从事岩土率相关理论及工程应用研究。E-mail:
Investigation into transmission coefficient of calcareous sand: waveform coupling effects and gradient boosting prediction method
Guo-jian SHAO , Ze-hui MAO, Yu-chen SU, Hong-cheng JIAO, Ya-ru LYU
Affiliations
  • College of Mechanics and Engineering Science, Hohai University, Nanjing, Jiangsu 211100, China
出版时间: 2025-11-14 doi: 10.16285/j.rsm.2024.1585
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应力波穿过材料前后的特征值变化是判断材料波衰减能力的重要依据,可通过霍普金森杆(split Hopkinson bar,简称SHPB)试验中透射波幅值与初始入射波幅值的比值(即透射系数)进行表征。然而,因透射系数与波形参数密切相关,目前还难以建立透射系数的定量表征方法。以多孔、不规则、易破碎的钙质砂为研究对象,通过物理试验和数值模拟相结合的方法,探究了脉宽、平台段时程、上升沿速率、下降沿速率、应力峰值以及中心对称轴对钙质砂透射系数的影响,发现透射系数随着应力波的脉宽和中心对称轴耦合作用、平台段时程和上升及下降沿速率耦合作用、脉宽和峰值应力耦合作用以及下降沿速率和脉宽耦合作用的响应明显,而随峰值应力、上升沿与下降沿速率三者耦合作用的响应不明显。针对波形参数难以完全解耦,提出了基于梯度提升算法的透射系数预测方法,可有效表征多因素耦合问题。当训练样本达到91个时,预测精度达到96%以上,可以很好地建立波形参数与透射系数的映射关系,为防护工程结构荷载设计计算提供参考依据。

钙质砂  /  透射系数  /  LS-DYNA有限元  /  SHPB冲击试验  /  梯度提升算法

The variation in characteristic values of stress waves before and after passing through a material serves as a critical basis for evaluating its wave attenuation capacity. This can be characterized by the ratio of transmitted wave amplitude to the initial incident wave amplitude (i.e., transmission coefficient) in SHPB tests. However, due to the close correlation between the transmission coefficient and waveform parameters, it remains challenging to establish a quantitative characterization method for the transmission coefficient. Therefore, this study focuses on porous, irregular, and fragile calcareous sand as the research object. By combining physical experiments with numerical simulations, we investigate the influence of pulse width, platform duration, rising edge rate, falling edge rate, peak stress, and the central axis of symmetry on the transmission coefficient of calcareous sand. It is found that the transmission coefficient responds significantly to the coupling effects of the pulse width and the central axis of symmetry of the stress wave, the coupling effects of the platform section duration and the rising and falling edge rates, the coupling effects of the pulse width and the peak stress, as well as the coupling effects of the falling edge rate and the pulse width. Conversely, the response to the coupled effects of peak stress, rising edge rate, and falling edge rate is not pronounced. Owing to the difficulty in completely decoupling these waveform parameters, a prediction method is proposed for the transmission coefficient based on the gradient boosting algorithm, which effectively addresses multi-factor coupling issues. When the number of training samples reaches 91, the prediction accuracy exceeds 96%, which can effectively establish the mapping relationship between waveform parameters and transmission coefficients, providing a reference basis for the load design and calculation of protective engineering structures.

calcareous sand  /  transmission coefficient  /  LS-DYNA finite element  /  SHPB impact test  /  gradient boosting algorithm
邵国建, 毛泽辉, 苏宇宸, 焦泓程, 吕亚茹. 钙质砂透射系数探究:波形耦合作用及梯度提升预测方法. 岩土力学, 2025 , 46 (11) : 3661 -3672 . DOI: 10.16285/j.rsm.2024.1585
Guo-jian SHAO, Ze-hui MAO, Yu-chen SU, Hong-cheng JIAO, Ya-ru LYU. Investigation into transmission coefficient of calcareous sand: waveform coupling effects and gradient boosting prediction method[J]. Rock and Soil Mechanics, 2025 , 46 (11) : 3661 -3672 . DOI: 10.16285/j.rsm.2024.1585
应力波穿过材料前后的特征值变化是判断材料波衰减能力的重要依据,可通过分离式霍普金森压杆(split Hopkinson pressure bar,简称SHPB)试验中透射波幅值与初始入射波幅值的比值(即透射系数)[1-4]进行表征。当前已采用SHPB试验对混凝土、岩石等块状材料透射系数进行了大量研究[5-11]
对于散体材料而言(如砂土),其材料透射系数的研究相对较少[12]。例如,Huang等[13]研究了不同幅值应力波在石英砂中的传播,发现颗粒破碎导致的能量消耗使得透射系数随着入射波幅值的增加而减少。Cui等14采用改良的SHPB装置通过能量吸收系数和透射系数定量表征了砂土在单次及重复冲击下的波传播特性。Chen等[15]通过中尺度数值模型分析了硅砂相对密度、脉宽与振幅对应力波衰减的影响,并提出了残余峰值应力、波速以及峰值应力速度随试样长度变化的衰减经验公式。Singh等[16]采用无量纲参数归一化实际距离,通过构建透射系数与无量纲参数间的映射关系,系统揭示了空气爆炸荷载作用下不同粒径范围干燥Badarpur砂的应力波衰减特性。此外,针对多孔、不规则、易破碎的海洋钙质砂[17-21],魏久淇等[22-23]通过对比不同应变率、密实度、含水率下钙质砂与石英砂的透射系数变化及能量吸收效率,发现钙质砂应力波衰减特性较之石英砂存在显著差异性。
为了得到砂土透射系数的量化表征方法,Lü等[24]基于大量SHPB试验,提出了钙质砂透射系数的半经验预测方程。于潇等[25-28]结合试验和数值仿真结果,探究了脉宽、振幅、相对密实度、应变率及粒径等因素对波透射系数的影响,并提出了一种量化钙质砂透射系数的新方法。上述研究虽已建立了砂土透射系数的预测框架,但尚未系统研究透射系数与应力波参数之间的关系。
鉴于此,本文以钙质砂为研究对象,采用一维侧限单脉冲SHPB试验和LS-DYNA有限元模型,系统分析了入射波波形参数(应力波时程(脉宽)、平台段时程、应力波上升沿速率、下降沿速率、峰值以及波形)对透射系数的影响。针对波形参数难以解耦的问题,采用梯度提升算法训练试验和计算结果,提出一种精确可靠的透射系数预测方法。
在SHPB试验中,透射系数可定义为[1-4]
式中:Tr为无量纲的透射系数;Im为入射杆中初始入射波幅值;Tm为透射杆中透射波幅值。
基于此,Lü等[24]给出了不同长度试样下透射系数的半经验计算方法:
式中:x为试样长度;D为试样直径;β为拟合得到的常数系数。所得半经验公式得到了试验结果的验证。
但该经验公式存在一定的局限性:其一,为了同时研究应力-应变特性,试样长度需满足3~5次的波反射,而不同工况下反射次数会影响透射系数的结果,如此确定的透射系数已不再表征试样的自身属性;其二,若增加试样长度以使其符合单脉冲传播的要求,那么SHPB冲击试验将难以测得透射波,数值模拟的情况亦是如此;其三,当试样长度足够长且满足单脉冲传播时,目前并没有通用规范来规定具体的取样长度,致使所得透射系数离散性极大,难以表述钙质砂的波衰减特性。
针对上述局限性问题,以干燥的钙质砂为试验材料,对其中应力波的衰减进行了初步试验。
试验所用钙质砂来源于我国南海某珊瑚岛礁,主要成分为CaCO3。鉴于原始钙质砂样本中包含诸多大直径之珊瑚及贝类等物质,为控制其均匀性,试验前先将原样自然风干,再筛选钙质砂砂样,保留0.18~1.18 mm的粒径区间。根据《土工试验方法标准》(GB/T50123-2019)[29]中颗粒分析试验的筛分法测得筛选后钙质砂的颗分曲线,见图1。根据该规范进行钙质砂的相对密度试验,测得其最大和最小干密度分别为1.389、1.049 g/cm3,并以90%的相对密实度配置试验所需试件。钙质砂颗粒具体物理参数如表1所示。
试验利用改进后的SHPB试验装置进行一维侧限单脉冲SHPB试验。入射杆及透射杆均采用直径为37 mm、长为3 000 mm的铝杆,子弹则采用直径为37 mm、长为600 mm的铝杆。
钙质砂试样采用新型螺纹拼接式套筒、圆柱体铝垫块以及硅胶止水垫圈进行装配,通过将硅胶止水垫圈与套筒内壁预留凹槽配合,并将铝垫块推入挤压硅胶止水垫圈使其产生径向变形,从而抱紧铝垫块,达到限位作用,方便组装外螺纹试样仓中钙质砂试样的装配。随后通过少量多次称取定量钙质砂进行分层装样,装样时将试样轻轻锤击并辅以敲击侧壁以达到指定高度[20]。最后重复上述步骤安装另一半套筒装置进行试验。
通过改变外螺纹试样仓长度来改变试验的试样长度,如图2所示。其中圆柱体铝垫块直径为37 mm,长为30 mm。由于考虑到摩擦的作用,故套筒内径略大于铝垫块和铝杆,为37.1 mm,壁厚为10 mm。试验所得初始波形曲线如图3所示。对比图4中曲线可知,与魏久淇等[22]研究结果类似,增加套筒和垫块后的空打波形与杆件空打时的基本重合,故套筒和垫块对试验结果的影响可忽略不计。
本文分别开展了试样长度为18、37、55、74、111 mm共计5种不同试样长度的一维侧限单脉冲SHPB试验。鉴于实际装样时难免存在误差,导致试样装样后的实际相对密实度偏离理想密实度。为此,本文特选取实际相对密实度与理想密实度较为接近的4~5组重复试验予以展示,相关试验工况汇总归纳于表2
根据试验结果并结合式(1)得到无量纲试样透射系数与试样长度的关系,如图5所示。可见,随试样长度的增加,其透射系数逐步降低,应力波衰减明显。试样长度为18 mm时,透射系数约为0.17;长度增至37 mm时,透射系数衰减至0.10左右;继续增加长度,透射系数衰减幅度逐渐变小,至111 mm时,透射系数已不足0.05。首先运用式(2)对试验结果予以拟合,见图5。发现通过短试样SHPB冲击试验拟合所得的试样透射系数与试样长度之间的关系式,无法有效表征单脉冲下的试验结果。因此,采用指数与常数项的关系式,重新构建了试样透射系数Tr与试样长度之间的关系:
式中:yAt为拟合得到的常数系数。通过该拟合公式,曲线调整后其相关系数R2在0.992以上。拟合曲线同样绘于图5中。
事实上,试样透射系数反映材料本身属性,不随试验和模拟技术的改变而改变。但已有研究表明,脉宽较短的入射波体现出了更理想的衰减效果,而振幅对应力波衰减效果不明显[26]。故入射波的波形参数会显著影响透射系数。由于试验难以控制入射波上升沿、下降沿速率等波形参数,目前尚未系统得到波形参数对应力波传播衰减规律的影响。
2.2节试验研究钙质砂透射系数时通过整形技术实现了梯形波加载,SHPB冲击试验时可通过改变子弹长度、子弹形状、整形器材料、整形器形状及厚度等方式实现方波、梯形波、半正弦波等波形加载[29-31],但难以定量构建理想的波形曲线和绝对相同的试样条件。因此,本文在保证试样完全相同(本构及参数不变)的前提下,采用数值模拟的方法定量研究波形参数对透射系数的影响。
图6所示,通过脉宽、应力上升沿速率、应力波峰值、平台段时程、应力下降沿速率以及波形对称与否6个参数确定入射波波形,通过数值模型对上述6个变量进行概化组合模拟,分析其对钙质砂透射系数的影响。设计计算方案时,因变量之间多存在耦合现象,任一变量改变都会导致其他变量的改变,故而难以实现单因素分析。具体模拟工况见表3,其中选取变量中可量化的某一项作为每组工况的区分项,即主要工况。
采用LS-DYNA显示动力分析程序建立砂土SHPB试验的三维有限元数值模型,如图7所示。数值模型包括入射杆、透射杆、试样以及侧限套筒4部分,尺寸与物理试验完全相同。数值模型各部分均采用Solid164三维实体单元。模型共计83 648个单元,为提高计算精度,对试样部分网格划分较细,共包含单元数5 868个,其他部分网格划分较疏,数值模拟的计算模型见表4。采用1/4对称模型,以减少计算量。在对称面上设置对称约束,限制对称面上节点在法向的位移。Lü等[19]采用数值模拟的方法对子弹撞击入射杆所得入射波与杆端输入入射波进行了比较,两者基本一致。因此,本模型没有考虑子弹撞击入射杆的过程,直接在入射杆的单元节点上输入相应入射波。
模型接触面包括试样与入射杆接触、试样与透射杆接触、试样与侧限套筒接触、侧限套筒与入射杆和透射杆的接触。基于SHPB物理试验特点,采用适用于碰撞和自接触问题的*CONTACT_AUTOMATIC_SINGLE_SURFACE模型[32]处理接触面的动态响应。依据一维应力波传播理论假设,设定无摩擦边界条件(摩擦系数为0),消除摩擦效应对透射系数的干扰。
入射杆、透射杆以及侧限钢套筒均采用*MAT_001(ELASTIC)本构模型,其中入射杆和透射杆材料与物理试验一致,均设定为密度ρ=2 700 kg/m3、弹性模量E=72 GPa、泊松比υ=0.32的铝合金。侧限套筒设为密度ρ=7 900 kg/m3、弹性模量E=205 GPa、泊松比υ=0.29的钢材。
采用*MAT_005(SOIL & FOAM)本构模型[33]表征钙质砂的冲击力学行为,该本构模型可以根据试验数据精准反演材料的压缩特性,在岩土冲击动力学领域具有成熟应用基础。由于透射系数作为材料固有属性参数,其数值受本构模型及参数标定影响显著,但本研究聚焦于波形参数对透射系数的影响机制,故未开展多本构模型对比分析。图8(a)为SOIL & FOAM本构模型静水压力-体积应变曲线示意图,模型假设加载和卸载曲线一致,冲击过程中试样体积不发生破碎,即体积破碎率(volume crushing ratio,简称VCR)为1。屈服函数Φ由静水压力P、第二不变量J2以及几个常数系数(a0a1a2)描述:
式中:σ1σ3分别为大、小主应力;Sij为偏应力;σx为测得的轴向应力,在试样均匀化加载的条件下与正应力相等,在屈服时σs=σxσs为屈服应力;σr为侧限压力;ξ为侧压力系数,定义为ξ=σr/σx,并通过SHPB试验确定ξ=0.495。
模型中,体积应变εkk由相对体积的自然对数表示。将计算开始时当前体积与初始体积的比率定义为相对体积。在压缩运动中,压力为正,体积应变为负[34],如下式所示:
式中:V为试样瞬时体积;V0为试样初始体积。
模型共需23个输入参数,即式(5)中的a0a1a2以及10组应力与相对体积应变对应关系下的加卸载曲线(EPS1~EPS10以及P1~P10),所有输入参数均可由试验测试校准。由于本文采用载荷曲线标识符(load curve ID,简称LCID)表征加载曲线,通过10组试验得到的应力-相对体积应变关系多段线性逼近理论结果[35-36],故本模型仅需对a0a1a2这3个输入参数进行标定。
根据应变率为610 s−1、相对密实度为90%的钙质砂SHPB冲击试验所得应力时程曲线和应力-应变曲线,转换为应力与体积应变的关系,通过调整系数进行数值模型材料参数的标定,钙质砂数值模型的材料参数如表5所示。标定前后应力-应变曲线,如图8(b)所示,标定后的数值模型与试验结果呈现良好一致性,其中轴向应变12%处的计算误差为14%,原因是SOIL & FOAM模型的本质是通过物理试验结果反向拟合本构模型参数,文中采用10组试验数据拟合得到的参数可以很好表征材料的冲击压缩特性,因数据点选取位置导致加载峰值点误差在14%左右,均在合理范围内。
为了研究峰值应力与上升、下降沿速率对透射系数的影响,计算了18、48、78 MPa 3种峰值应力下对称三角形入射波下的透射系数,应力波对称中心轴位置对应的时程为60 μs、脉宽为100 μs、平台段时程为0 μs,如图9(a)所示。结果发现在数值模型上入射杆所得入射应力波和透射杆所得透射应力波与试验一致。共考虑11个试样长度,共计33种工况,见表3
图9(b)为该工况下透射系数随试样长度的模拟结果及拟合曲线,由数值计算得到试样长度分别为18、38、54、72、111 mm的钙质砂透射系数分别为0.220、0.144、0.099、0.081、0.054,与试验结果具有良好的一致性,印证了数值模型及模型参数的合理性。由于入射波形参数是多重变量耦合,且为了验证修订后的半经验式(3)是否适用于该复杂工况下透射系数与试样长度之间的关系表征,对数值结果进行拟合,曲线调整后其相关系数R2在0.979以上。再次验证了半经验公式的可靠性。所有工况下的拟合参数见表6
对比不同峰值应力下透射系数3条曲线可以发现,随着应力峰值的增加,不同长度试样的透射系数仅在线形变化段上有细微差别,随着试样长度的增加,3种工况下钙质砂的透射系数偏差不断减小,直至完全重合,此现象与Chen等[15]所得的研究结果相似。说明在应力波对称中心轴及脉宽相同的情况下,试样的峰值应力大小对试样透射系数的影响不明显。
为了研究平台段时程对透射系数的影响,图10(a)给出了3种平台段时程下的对称入射波形,即0、100、150 μs,控制应力波对称中心轴时程为100 μs、脉宽为200 μs、峰值应力为78 MPa。随着平台段时程的改变,入射应力波由三角形波变为梯形波,入射应力波上升及下降沿速率随之改变。本节计算7个试样长度,共计21种工况,具体见表3
图10(b)为透射系数计算结果及拟合曲线。随着平台段时程的增加,入射应力波的上升、下降速率随之增加,透射系数不断增大,应力波衰减率不断降低,达到平缓状态所需的试样长度不断变长。随着试样长度的增加,钙质砂的透射系数逐渐降低,且拟合曲线的趋势随平台段时程的增加而变得平缓,逐渐趋于线性相关。与图9(b)不同的是,3条曲线的后段未呈现显著的平缓段态势,这表明平台段时程不仅对试样透射系数的大小产生影响,还会减缓透射系数随试样长度的变化趋势。
图11(a)通过将应力峰值控制在78 MPa且采用对称三角形波,研究了100、150、200 µs 3种脉宽以及7个试样长度与透射系数之间的关系,共计21种工况,详情见表3。其中,上升沿、下降沿速率以及应力波对称轴(t分别为50、75、100 µs)会随着脉宽的改变而一同变化。
图11(b)为该工况下透射系数随试样长度的结果及拟合曲线。随着入射应力波脉宽的增加,透射系数随试样长度的变化曲线出现上移,且在一定试样长度范围内,3种工况下透射系数的变化幅度基本相同。例如,试样长度为38 mm时,3种脉宽下的透射系数之比为1.0∶2.1∶3.0;当试样长度为54 mm时,该比例为1.0∶2.1∶2.9。此变化量随试样长度增加而减小,如试样长度为111 mm和144 mm时,三者之比分别为1.0∶1.63∶2.0和1.0∶1.64∶2.0。说明脉宽对透射系数的影响近似呈线性关系,而产生偏差的原因可能是入射应力波的上升沿、下降沿速率随脉宽改变所致。对比图9(b)可说明,相较于峰值应力以及上升沿、下降沿速率耦合作用对透射系数的影响,脉宽与上升沿、下降沿速率的耦合作用对透射系数的影响更为显著。
为探究应力峰值与脉宽对透射系数的作用机制,在保证入射应力波具有相同上升沿与下降沿速率的条件下,模拟了应力峰值依次为18、48、78 MPa的对称三角形入射波,其对称中心轴位置对应的时程分别设定为23、62、100 µs处,同时脉宽分别设定为46、124、200 µs,如图12(a)所示。共探究7个试样长度,涉及21种工况,具体见表3
图12(b)呈现了该工况下透射系数随试样长度变化的实验结果。随着脉宽与峰值应力的增大,在试样长度较短区间内,透射系数随试样长度增长呈现明显上升态势;但随着试样长度进一步增加,钙质砂的透射系数逐渐下降,且3条曲线两两之间呈现出不同规律。对比应力峰值分别为18、48 MPa的工况拟合曲线,可发现两者近乎平行,由此推测应力峰值和脉宽的变化主要影响透射系数的具体数值,而不改变其随试样长度变化的总体趋势。对比应力峰值48、78 MPa的工况曲线,规律则有所不同。在曲线初始阶段,两者存在显著差异,但随着试样长度持续增加,两条曲线逐渐趋于重合,最终在试样长度达111 mm时完全重合。结合图9(b)的分析,可推测造成此现象的原因可能为:在应力峰值与脉宽的比例未达特定阈值前,脉宽是主导透射系数变化的关键因素,主要影响曲线的数值水平;而当该比例超过阈值后,应力峰值成为决定曲线线形趋势的主导因素。
为研究入射应力波的下降沿速率及脉宽对透射系数的影响,图13(a)展示了在固定应力峰值为78 MPa且保持入射波上升沿速率一致的条件下,对3种不同下降沿速率下透射系数与试样长度之间关系的计算结果。在此设定下,入射应力波形由常规的对称三角形波转变为不对称三角形波,同时伴随着脉宽分别变为100、150、200 µs。共模拟7个试样长度,21种工况,具体见表3
图13(b)呈现了该工况下透射系数随试样长度变化的曲线。可以发现,透射系数与入射波下降沿速率呈正相关关系。随着入射波下降沿速率降低,入射应力波由对称形态转变为不对称形态,此过程中透射系数显著下降,且曲线线性趋势亦发生明显变化。结合图12(b)综合分析可推测:在入射应力波上升速率恒定条件下,透射系数变化趋势受应力峰值与脉宽共同影响。应力峰值和脉宽增加时,透射系数呈增大趋势;而当入射应力波下降沿速率减小且脉宽增加时,透射系数呈减小趋势。这清晰地表明,入射应力波下降沿速率相较于脉宽,对透射系数数值的影响更为显著,且二者对透射系数的影响呈相反态势。
鉴于波形参数间难以解耦,无法得到某一变量对透射系数的影响。机器学习算法凭借其强大的非线性拟合与自适应学习能力,为解决多因素耦合问题提供了有效途径。例如,Yu等[37-38]运用多种机器学习方法,如反向传播神经网络(back propagation neural network,简称BPNN)、决策树(decision tree,简称DT)、随机森林(random forest,简称RF)、逻辑回归(logistic regression,简称LR)、岭回归(ridge regression,简称RR)、K近邻算法(K-nearest neighbors,简称KNN)、极端梯度提升(extreme gradient boosting,简称XGBoost)等,系统地揭示了多场耦合下氯离子在钢筋混凝土结构中的扩散规律及其对结构使用寿命的影响。作为集成学习方法,梯度提升算法通过叠加弱分类器提升预测精度,支持任意可微分损失函数与弱分类器,兼具灵活性与可释性。该算法以损失函数、弱分类器和加法模型为核心要素,通过迭代拟合残差、沿损失函数负梯度方向更新模型,逐步逼近最优解,在回归与分类任务中应用广泛[39-41]。故本研究基于梯度提升算法对不同波形参数下钙质砂透射系数进行预测。首先输入前文计算与试验结果训练初始模型并计算梯度(残差),随后以梯度为目标训练新模型并与原模型加权组合,不断重复直至满足停止条件。其算法步骤主要分为以下3步:
(1)通过最小化损失函数Lziγ)对所有的N个样本点求和来确定初始函数值。这里的z是一个变量,通过对γ的选择使得损失函数总和最小,从而确定初始函数f0x):
(2)对于每个迭代步骤,从m=1~M,首先计算负梯度,具体如下:
其中,对于每个样本点i,计算损失函数对前一步得到的函数fm−1xi)的偏导数,并取负值得到。这个值代表了当前模型在样本点i处的误差方向。通过最小化平方误差,用集成学习中的基础组件(基学习器)hmx)确定参数ω并拟合,具体是对所有样本点的求和,找到使得这个和最小的参数ωm
使用Line search确定步长ρm,通过最小化损失函数L来确定步长ρ的值,使得在当前迭代步骤中,损失函数在fm−1xi)的基础上加上步长与基学习器乘积后的结果最小:
将前一步的函数fm−1xi)加上步长ρm与基学习器hmxiω)的乘积,得到新的函数fmx),用于下一次迭代。
(3)输出fmx),这个函数是经过多次迭代不断优化得到的结果,可以用于对未知数据进行预测等任务。
图14为透射系数预测结果。其中,图14(a)为97组训练集、11组测试集所得结果,与试验结果对比发现预测结果与试验结果较好吻合,准确率Acc(accuracy)达到了96.2%。图14(b)为91组训练集、17组测试集所得结果,发现预测精度为96.9%。由此可见,预测精度与样本数量并非正相关,且计算时间均小于3 min,因此此处不再对计算效率进行讨论。两次预测的准确性均在96%以上,表明梯度提升算法能够较好的预测钙质砂的透射系数。
本文基于LS-DYNA有限元程序,对钙质砂的透射系数进行模拟分析,研究了脉宽、平台段时程、上升沿速率、下降沿速率、应力峰值、应力波中心对称轴以及波形对透射系数的影响。针对参数无法解耦问题,采用梯度提升算法对钙质砂透射系数进行了学习和预测。得出以下主要结论:
(1)应力峰值在试样较短时对透射系数影响显著,随试样增长该影响差异渐趋消失;透射系数与平台段时程正相关,拟合曲线随试样长度增加趋于平缓;脉宽对透射系数影响近似线性,其增量随试样长度增长趋于稳定;当应力峰值与脉宽耦合作用时,在试样较短时脉宽为主导因素,随着试样长度增加应力峰值渐为主导因素;入射应力波形态改变或保持上升沿速率不变仅下降沿速率变化均会改变透射系数随试样长度的变化趋势。
(2)针对多波形因素耦合作用下透射系数的变化,对透射系数随长度对数下降的半经验计算方法进行了修正,使透射系数的估算结果能够适用多波形因素耦合变化,拟合曲线调整后其相关系数R2均在0.979以上,可以较好的表征其内在关系。
(3)针对入射应力波波形参数间难以解耦问题,提出了基于梯度提升算法的钙质砂透射系数预测方法。结果表明,当训练集为91个时,预测精度达到96%以上,说明该模型可以有效地从训练数据中学习到波形参数与透射系数间的复杂关系,从而对透射系数进行准确的预测,为工程设计计算提供透射系数估算方法。
(4)通过对波形参数与钙质砂透射系数关联性的系统研究,得以剖析在多种不同冲击条件(即不同的应力波波形条件)下,何种透射系数可被遴选为设计参数。且波形参数的影响规律,可以应用于其他土体,使用时仅需对该土体开展一组SHPB冲击试验标定其参数,预测所得透射系数是防护工程结构荷载设计计算的重要依据。
  • 国家自然科学基金面上项目(52279097; 51779264)
  • 江苏高校“青蓝工程”
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2025年第46卷第11期
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doi: 10.16285/j.rsm.2024.1585
  • 接收时间:2024-12-24
  • 首发时间:2026-03-27
  • 出版时间:2025-11-14
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  • 收稿日期:2024-12-24
  • 录用日期:2025-06-06
基金
Natural Science Foundation of China(52279097; 51779264)
国家自然科学基金面上项目(52279097; 51779264)
Jiangsu Province “Qing Lan Project”
江苏高校“青蓝工程”
作者信息
    河海大学 力学与工程科学学院,江苏 南京 211100

通讯作者:

吕亚茹,女,1987年生,博士,教授,主要从事岩土率相关理论及工程应用研究。E-mail:
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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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