Article(id=1209811348960178756, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1209811339510411616, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2408640, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1731945600000, receivedDateStr=2024-11-19, revisedDate=1735747200000, revisedDateStr=2025-01-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1766371102800, onlineDateStr=2025-12-22, pubDate=1751904000000, pubDateStr=2025-07-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766371102800, onlineIssueDateStr=2025-12-22, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766371102800, creator=13701087609, updateTime=1766371102800, updator=13701087609, issue=Issue{id=1209811339510411616, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='19', pageStart='7885', pageEnd='8315', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766371100547, creator=13701087609, updateTime=1766373228996, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1209820266960654935, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1209811339510411616, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1209820266960654936, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1209811339510411616, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=7995, endPage=8002, ext={EN=ArticleExt(id=1209811350830838410, articleId=1209811348960178756, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Experimental Study on Rainfall-induced Slope Instability Model Based on 3D Laser Scanning Technology, columnId=1209811350717592194, journalTitle=Science Technology and Engineering, columnName=Papers∙Agricultural Science, runingTitle=null, highlight=null, articleAbstract=

In order to explore the deformation and failure mechanisms, as well as degradation characteristics of silt slopes under rainfall conditions, a large-scale slope model test apparatus was designed with silt slopes as the research subject. Multi-sensor internal monitoring and 3D laser scanning technology were applied. During slope instability under a rainfall intensity of 30 mm/h, data on moisture content, pore water pressure, soil pressure, and deformation and failure characteristics at various slope locations were collected. Results indicate that sensors at the slope toe have the fastest response, showing the highest rate of change. Rainwater accumulates at the slope toe, causing horizontal seepage, which leads to rapid increases in moisture content at the toe and lower middle sections of the slope, along with a reduction in soil shear strength. Under rainfall intensity conditions, the deformation and failure of silty slopes initiate at the slope toe, where small-scale collapses first occur. These progressively develop into transverse through-cracks, accompanied by minor-scale failures that extend upslope. Ultimately, these processes lead to overall slope failure. The findings offer theoretical insights to support engineering construction and protection in silty slope regions.

, correspAuthors=Ji-peng WANG, 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=Xian-wei LI, Xu-guang GAO, Ji-peng WANG, Hai-chao SHANG, Jing JING, Yan ZHANG), CN=ArticleExt(id=1209811354458911545, articleId=1209811348960178756, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于三维激光扫描技术的降雨诱发边坡失稳模型试验研究, columnId=1209811350918918803, journalTitle=科学技术与工程, columnName=论文∙农业科学, runingTitle=null, highlight=null, articleAbstract=

为探究粉土质边坡在降雨条件下的变形破坏机理和劣化特征,以粉土质边坡为研究对象,通过设计大型边坡模型试验装置并结合多传感器内部监测和三维激光扫描技术,获取了30 mm/h降雨强度条件下边坡失稳过程中不同位置处的含水率、孔隙水压力、土压力及变形破坏特征。试验结果表明:坡脚处的传感器响应最快,变化速率最大。雨水在坡脚汇集后,水平方向发生渗流,导致坡脚和坡中底部含水率短时间内升高,土体抗剪强度降低。因此,降雨强度条件下粉土质边坡变形破坏从坡脚开始,首先发生小范围坍塌,逐渐形成贯穿式横向裂缝,过程中伴随着向坡体上方的小规模破坏,最终发生整体破坏。研究结果可为粉土质边坡地区的工程建设和防护提供一定的理论依据。

, correspAuthors=王冀鹏, authorNote=null, correspAuthorsNote=
* 王冀鹏(1988—),男,汉族,河北邯郸人,博士,教授。研究方向:非饱和土力学的微宏观试验等。E-mail:
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李现伟(2000—),男,汉族,山东聊城人,硕士研究生。研究方向:植被与土相互作用的水力和力学特性。E-mail:

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李现伟(2000—),男,汉族,山东聊城人,硕士研究生。研究方向:植被与土相互作用的水力和力学特性。E-mail:

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Measurement results of rainfall uniformity

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降雨强度/
(mm·h-1)
均匀度 降雨强度/
(mm·h-1)
均匀度
30 0.86 100 0.76
60 0.82 120 0.78
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降雨均匀度测定结果

, figureFileSmall=null, figureFileBig=null, tableContent=
降雨强度/
(mm·h-1)
均匀度 降雨强度/
(mm·h-1)
均匀度
30 0.86 100 0.76
60 0.82 120 0.78
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Physical properties of experimental soil

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最大干密度/
(g·cm-3)
最优含
水率/%
比重
Gs
黏聚力/
kPa
内摩擦角/
(°)
1.56 15.32 2.696 4.50 34.7
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试验用土物理性质

, figureFileSmall=null, figureFileBig=null, tableContent=
最大干密度/
(g·cm-3)
最优含
水率/%
比重
Gs
黏聚力/
kPa
内摩擦角/
(°)
1.56 15.32 2.696 4.50 34.7
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基于三维激光扫描技术的降雨诱发边坡失稳模型试验研究
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李现伟 1 , 高旭光 1 , 王冀鹏 1, * , 商海潮 1 , 荆靖 2 , 张岩 2
科学技术与工程 | 论文∙农业科学 2025,25(19): 7995-8002
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科学技术与工程 | 论文∙农业科学 2025, 25(19): 7995-8002
基于三维激光扫描技术的降雨诱发边坡失稳模型试验研究
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李现伟1 , 高旭光1, 王冀鹏1, * , 商海潮1, 荆靖2, 张岩2
作者信息
  • 1 山东大学土建与水利学院, 济南 250061
  • 2 山东省高速养护集团有限公司, 济南 250032
  • 李现伟(2000—),男,汉族,山东聊城人,硕士研究生。研究方向:植被与土相互作用的水力和力学特性。E-mail:

通讯作者:

* 王冀鹏(1988—),男,汉族,河北邯郸人,博士,教授。研究方向:非饱和土力学的微宏观试验等。E-mail:
Experimental Study on Rainfall-induced Slope Instability Model Based on 3D Laser Scanning Technology
Xian-wei LI1 , Xu-guang GAO1, Ji-peng WANG1, * , Hai-chao SHANG1, Jing JING2, Yan ZHANG2
Affiliations
  • 1 School of Civil Engineering, Shandong University, Jinan 250061, China
  • 2 Shandong Hi-Speed Maintenance Group Co., Ltd., Jinan 250032, China
出版时间: 2025-07-08 doi: 10.12404/j.issn.1671-1815.2408640
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为探究粉土质边坡在降雨条件下的变形破坏机理和劣化特征,以粉土质边坡为研究对象,通过设计大型边坡模型试验装置并结合多传感器内部监测和三维激光扫描技术,获取了30 mm/h降雨强度条件下边坡失稳过程中不同位置处的含水率、孔隙水压力、土压力及变形破坏特征。试验结果表明:坡脚处的传感器响应最快,变化速率最大。雨水在坡脚汇集后,水平方向发生渗流,导致坡脚和坡中底部含水率短时间内升高,土体抗剪强度降低。因此,降雨强度条件下粉土质边坡变形破坏从坡脚开始,首先发生小范围坍塌,逐渐形成贯穿式横向裂缝,过程中伴随着向坡体上方的小规模破坏,最终发生整体破坏。研究结果可为粉土质边坡地区的工程建设和防护提供一定的理论依据。

降雨入渗  /  模型试验  /  三维激光扫描技术  /  粉质边坡

In order to explore the deformation and failure mechanisms, as well as degradation characteristics of silt slopes under rainfall conditions, a large-scale slope model test apparatus was designed with silt slopes as the research subject. Multi-sensor internal monitoring and 3D laser scanning technology were applied. During slope instability under a rainfall intensity of 30 mm/h, data on moisture content, pore water pressure, soil pressure, and deformation and failure characteristics at various slope locations were collected. Results indicate that sensors at the slope toe have the fastest response, showing the highest rate of change. Rainwater accumulates at the slope toe, causing horizontal seepage, which leads to rapid increases in moisture content at the toe and lower middle sections of the slope, along with a reduction in soil shear strength. Under rainfall intensity conditions, the deformation and failure of silty slopes initiate at the slope toe, where small-scale collapses first occur. These progressively develop into transverse through-cracks, accompanied by minor-scale failures that extend upslope. Ultimately, these processes lead to overall slope failure. The findings offer theoretical insights to support engineering construction and protection in silty slope regions.

rainfall infiltration  /  model testing  /  3D laser scanning technology  /  silty slope
李现伟, 高旭光, 王冀鹏, 商海潮, 荆靖, 张岩. 基于三维激光扫描技术的降雨诱发边坡失稳模型试验研究. 科学技术与工程, 2025 , 25 (19) : 7995 -8002 . DOI: 10.12404/j.issn.1671-1815.2408640
Xian-wei LI, Xu-guang GAO, Ji-peng WANG, Hai-chao SHANG, Jing JING, Yan ZHANG. Experimental Study on Rainfall-induced Slope Instability Model Based on 3D Laser Scanning Technology[J]. Science Technology and Engineering, 2025 , 25 (19) : 7995 -8002 . DOI: 10.12404/j.issn.1671-1815.2408640
边坡失稳是全球范围内较为频发的自然灾害之一,对人类生命财产安全和居住环境构成了严重威胁[1]。降雨是其发生的最主要诱因,雨水入渗导致边坡内湿润锋下移,土体含水量增加,基质吸力减小,土体强度降低,造成边坡失稳[2-5]。因此,深入研究边坡在降雨条件下的水力-力学特征及其变形破坏模式至关重要。
目前,现场原位监测、室内模型试验、数值模拟和理论推导是常见的边坡稳定研究方法。但原位监测试验无法过多干预外界因素,数值模拟又难以直观地反映边坡真实的劣化特征。因此,研究人员多采用室内模型试验开展研究。林鸿州等[6]、方兴杰等[7]分别开展了不同坡面形态的细砂边坡模型试验,揭示了合适雨量预警参数及边坡破坏特征。蒋臻蔚等[8]开展了模型冲刷试验,探究了黄土路面细沟的发育过程及特征。王斌等[9]研究了不同级配堆积体下的降雨边坡失稳与破坏机制。刘洪华等[10]通过大型模型试验,研究了极端降雨诱发花岗岩类滑坡的机理与降雨成灾过程,周春梅等[11]通过室内单滴降雨模型试验,探究了降雨侵蚀对黄土变形破坏的规律。张永闯[12]针对边坡基底与上部风化土层的渗透性存在明显差异的现象,实施了全尺寸斜面模型降雨渗透试验,探究了泥石流发生的机理。李卓等[13]通过自行研制的模型试验装置开展了降雨试验,研究发现前期降雨是导致边坡滑坡的主要原因。
近年来,随着高速摄像机和三维激光扫描等高精度、非接触式测量技术的发展,部分学者开始将其应用于边坡模型试验[14-15]。这些技术在空间信息采集方面能够弥补传统监测方法的不足,特别是在捕捉边坡动态劣化过程和提高空间分辨率方面,具有显著优势。周杨等[16]结合了传感器的水文监测和三维激光扫描仪的变形监测,开展人工降雨模型试验,分析了降雨入渗速度对黄土边坡稳定性的影响。陈林万等[17]通过传感器监测、三维激光扫描等手段研究了降雨条件下黄土边坡的失稳过程。
综上所述,现有的研究对黄土以及细砂等边坡在降雨条件下的失稳机制已有较为深入的探索。然而,对于粉土质边坡失稳的研究相对较少,需要进一步开展系统的研究。因此,通过设计大型边坡模型试验装置,并结合多传感器内部监测和三维激光扫描技术,探究粉土质边坡在降雨条件下的变形破坏机理和劣化特征,为粉土质边坡地区的工程建设和防护提供理论依据。
长方体试验模型箱有效尺寸为3.0 m×1.5 m×1.5 m,主体由方形钢管焊接而成,两侧装有厚度为30 mm的透明钢化玻璃,顶面与一侧敞开,其余部位密封良好。模型箱底板厚度为5 mm,距地面0.2 m;敞口一侧挡板高度为0.2 m。此外,模型箱配套一伸缩棚,以满足遮雨、挡风及试验过程摄像采光的要求,边坡模型装置如图1所示。
降雨采用NLJY-10型人工模拟降雨系统(图2),主要由降雨架、水路管网、压力水泵、电子雨量计和旋转喷头等组成。降雨架长4 m×3 m×3.2 m,该系统可模拟降雨强度范围为5~240 mm/h,通过自动化控制中心调节喷头开度和水泵压力,控制降雨强度、均匀性及雨滴大小,分辨率为0.1 mm。
降雨均匀性是模拟天然降雨的关键指标之一,根据《喷灌工程技术规范》(GB/T 50085—2007)[18],工程上一般要求降雨均匀系数不低于80%才可以用于试验中。用自制雨量简来收集雨水,降雨时间 20 min,在测试时将自制雨量筒均匀分布在模型箱内,调整降雨装置的开度使其达到要求的降雨强度,计算均匀度测试各个雨强下的均匀度[19],如表1所示。依据山东地区的降雨统计资料,本次模拟实验主要选择30 mm/h雨强作为试验所用,测试该雨强下整体降雨的均匀性为86%,符合要求。
采用三维激光扫描仪测量坡面的三维变形。三维激光扫描仪通过激光测距的原理,由仪器投射出的激光先是到达被测物体的表面,继而反射回扫描仪内的传感器中,扫描仪据此计算其与物体的距离,确定物体在空间中的位置,得到三维点云数据。该技术的优点在于能够快速、高效和精准地获取到被测物体表面大量密集点的三维坐标、反射率和纹理等几何形态信息,复建出被测目标的三维模型及线、面、体等各种数据。通过对边坡降雨破坏前后的点云数据进行叠加和比较,可以实现对边坡动态变形演化的监测分析。
试验用土取自济南黄河河务局遥墙段黄河冲淤积粉土,依据《土工试验方法标准》(GB/T 50123—2019)[20],开展室内物理力学性质试验得到试验用土的基本性质,试样密度、含水率、黏聚力和内摩擦角等基本参数如表2所示。颗粒级配曲线如图3所示,粒径主要分布在0.05~0.25 mm的粒径范围内,约占总质量的95%,属于级配不良土,具有粒径分布不均匀、级配差的特点。
试验前对土样过筛,去除石头、植物根系和落叶等杂物。过筛后配置含水率为18.5%的土体,静置48 h。模型填筑采用分层击实法,每层填筑厚度10 cm,共填筑12层。夯实中对于边界及角落处等特殊部位进行重点夯实,填筑下一层之前,对上一层的层面进行刮毛处理。本试验所采用压实度为 90%。填筑完成后进行坡面削坡,保证坡面平整并覆盖薄膜,静置40 h。
试验中所使用的传感器包括土压力盒、体积含水率传感器、孔隙水压力传感器和土水势传感器,按照设计布置图埋设于填筑过程中,如图4所示。为了保证传感器的走线对试验影响尽可能小,传感器的数据线从边坡坡顶后方位置布设,试验设置数据采集间隔为1 min。在边坡模型上方安装三维激光扫描仪测量坡面的三维变形。
边坡测点土壤体积含水率变化如图5所示。在30 mm/h降雨强度下,坡脚剖面5、10 cm处的土壤含水率传感器分别在降雨8、14 min时响应,此后含水率经历了较快的增长阶段。并且,埋设深度5、10 cm的传感器分别在114、49 min达到相对稳定。坡中剖面10、20、100 cm处的土壤含水率传感器分别在降雨9、15、35 min和响应。坡中100 cm处的含水率传感器在响应后数值迅速增大,于141 min达到相对稳定,该剖面的其余2个含水率传感器分别在340、290 min时测量数值发生波动,这可能是长期降雨导致的坡中浅层土体破坏,使坡中10、20 cm处传感器位置发生变化,但随着降雨的进行传感器又被上层垮塌土体覆盖。坡肩剖面10、20、30、50、70、100 cm处的土壤含水率传感器分别在降雨60、104、98、188、121 min时响应。坡肩位置处的含水率均呈现出随着边坡深度增加而增长速率变缓的特点,在坡肩100 cm出现了缓慢增长的平台期。坡顶剖面20、50cm处的土壤含水率传感器分别在降雨143、212 min时响应,最终达到相对的稳定状态。
边坡含水率随降雨时间的变化关系如图5(e) 所示。不同位置处土壤初始含水率随着深度的增加而增大,这可能是由于模型填筑后进行了静置,导致土体中的水分随自身重力向下发生了迁移。相同埋设深度的含水率传感器越靠近坡脚响应过程越短,呈现出快速增大至饱和状态的特点。
在降雨进行到200 min后,坡肩10 cm和坡顶20 cm处均出现缓慢增长平台,但坡顶20 cm处响应时间滞后于坡肩10 cm处,两者平台期持续时间基本一致。这是由于在降雨前期,边坡土体在非饱和状态下的渗透能力低于降雨的强度。随着雨水的入渗,表层土体的含水率逐渐上升,但尚未达到饱和状态。同时,土体非饱和渗透的能力也会随着含水率的增加而逐渐增加,直到与当前位置处的雨水入渗强度相同。此时,雨水便会从该剖面位置处的土体渗透至更深处的土层,导致浅层土体的含水率保持在动态稳定状态,而较深层土体的含水率则出现较快的上升。
边坡不同位置处孔隙水压力随降雨时间变化如图6所示。降雨开始后,埋设于坡脚20 cm处的孔隙水压力传感器响应最快,在降雨50 min时,孔隙水压力增长速率达到最大,降雨80 min时,增长速率减缓,呈现先大后小的特点。该位置孔隙水压力的增长速率比其他位置快,这是因为坡脚处从22 min开始出现积水,雨水渗到深部使得该处土体孔隙水压力率先开始增长且增长速度较快。由于坡脚从80 min时发生破坏,该处的孔隙水压力传感器随着坡面逐渐垮塌而向前滑移,其上方土体厚度逐渐增加,数值仍不断增大,但增长速率较坡脚破坏前有所减小。埋设于坡肩20 cm处的孔隙水压力传感器在降雨450 min时响应,响应时间最长,经历缓慢增长后坡肩破坏进而使传感器数据产生波动。
此外,坡中50 cm埋设的传感器响应时间快于坡中埋设20 cm处的传感器,该现象是由于降雨导致的坡脚积水水平渗流,并且渗流路径从坡底逐渐向坡体内部深处渗流且坡脚处渗流速度最大。
坡中和坡肩20 cm处孔隙水压力传感器响应后的增长速率均低于其各自剖面更深处传感器的增长速率,这可能与土体渗透路径和应力条件有关,浅层土体所受上覆压力较小,土体颗粒间的孔隙较大,容易被压缩。因此,浅层土体内水分进入或排出相对迅速,可以在周围的孔隙内进行扩散,孔隙水压力短时间内不会产生大的变化。此外,各传感器的孔隙水压力初始值均为负值,这是由于降雨前土体含水率低,土壤孔隙多被空气填充,土体颗粒间通过毛细作用的张力使孔隙水处于负压状态。随着降雨的进行,各传感器的孔隙水压力值均从开始的负值逐渐增大到正值,说明在降雨作用下随着时间的延长,土壤孔隙逐渐被水分填充,饱和度逐渐增大,毛细作用带来的张力变小,孔隙水压力由负转正。正孔隙水压力表示水分的压力大于周围土粒的接触压力,意味着周围土体承受来自水分的压力。
边坡不同位置处土压力随降雨时间变化如图7所示。在降雨试验开始前,不同位置处土压力传感器数值根据埋设深度成线性增加,埋设最深的坡顶100 cm处的土压力传感器数值最大,埋设最浅的坡中、坡肩和坡顶20 cm处的土压力传感器数值最小。但是,同样埋深20 cm的坡脚处土压力传感器数值大于其他相同埋设深度传感器的数值,这可能与模型填筑后的静置时间有关,土体水分向下迁移,使得坡脚处土压力在一定程度内增加。在30 mm/h降雨强度的条件下,随着雨水不断渗入土体内部,导致土体容重有所增加,边坡不同位置处的土压力均逐渐增大。其中,受含水率快速增加的影响,坡脚位置的土压力值增幅较快,在坡脚土体含水率饱和后,土压力达到相对稳定状态;此后,随着边坡内部含水率的不断增加,坡体的自重应力增大,抗剪强度降低,使得边坡垮塌并在坡脚位置淤积,坡脚的土层厚度增加,坡脚位置的土压力继续增加。
但是,在坡中和坡肩位置处,随着土体含水率和孔隙水压力的持续增加,土压力增加速率却相对较缓,这将导致土体的有效应力持续降低,进一步影响了土体抗剪强度和承载能力,使得边坡土体由稳定向不稳定过渡发展。最终,在降雨进行到425 min时,坡中相应位置发生垮塌破坏,传感器上部土体滑移到下部坡脚处,土压力开始急剧下降。坡顶不同深度处土压力随着含水率增加近似线性增加。
基于降雨诱发边坡变形破坏试验,总结边坡失稳模式如图8所示。可以看出,边坡破坏变形主要经历了3个阶段:①坡脚小范围垮塌;②坡脚滑移;③边坡整体破坏。降雨50 min时,由于坡面雨水在坡脚平台处持续汇集,水平方向也开始发生渗流,直接导致坡脚土体逐渐吸湿软化并出现小范围垮塌,形成横向张裂缝,这与此处孔隙水压力的迅速上升导致的土体强度降低相对应。随着降雨的进行,横向张裂缝逐渐扩大至整个坡脚。坡脚发生破坏后,上方土体失去有效支撑,在持续降雨条件下易形成空洞。由于坡脚失稳,边坡变形云图显示其上方区域的应力显著增加,从而促使变形与破坏逐步向坡面上方演化。随着破坏的扩展,坍塌的土体逐渐在坡脚处堆积。
经三维激光扫描仪扫描处理后,本次试验的点云数据如图9所示。试验之前对边坡进行扫描,之后将试验期间的数据与开始之前的数据进行对比,得出试验过程中边坡变化的模型。结合云图颜色变化与图例位移区间分布百分比,能够动态捕捉边坡坡面破坏演化过程,如图10所示。坡脚小范围垮塌时,坡面位移在1.13 cm内的分布点数占比92.6%,边坡破坏时坡面位移达到3.96cm以上的分布点数占比59.4%,当边坡整体破坏时,最大位移达25.7 cm。在边坡失稳破坏的3个主要阶段中,其力学机制分别表现为剪切破坏与拉伸破坏的耦合、以滑移破坏为主的剪切破坏,以及伴随大规模塑性变形的非均匀剪切破坏。
(1)边坡各位置的土壤体积含水率和孔隙水压力变化具有层次性。含水率随降雨时间的增加逐步上升,且越靠近坡脚,传感器响应时间越短,增速越大。部分浅层区域如坡肩出现增长平台期,随后逐渐稳定。孔隙水压力开始为负值,随着持续降雨边坡不同位置处孔隙水压力均增长为正值。
(2)坡体不同位置的土压力随时间和含水率变化。初始时刻土压力与深度线性相关,坡顶深处土压力最大。降雨入渗增大了土体容重,土压力逐渐增加,坡脚处因含水率上升而压力快速增大,达到饱和后趋于稳定。随着坡体垮塌并在坡脚堆积,坡脚土压力继续增加。坡中和坡肩位置土压力增速较缓,发生垮塌时急剧下降,而坡顶未发生垮塌使得坡顶底部土压力持续增加。
(3)降雨过程中,坡脚最先发生破坏,进而向边坡坡肩发生渐进性牵引式滑移破坏,主要可以分为3个阶段:坡脚小范围垮塌、坡脚滑移和边坡整体破坏。因此,边坡工程建设中坡脚的防护对于防止滑坡、水土流失和提高工程稳定性至关重要。
  • 国家重点研发计划政府间重点专项(2021YFE0194300)
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doi: 10.12404/j.issn.1671-1815.2408640
  • 接收时间:2024-11-19
  • 首发时间:2025-12-22
  • 出版时间:2025-07-08
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  • 收稿日期:2024-11-19
  • 修回日期:2025-01-02
基金
国家重点研发计划政府间重点专项(2021YFE0194300)
作者信息
    1 山东大学土建与水利学院, 济南 250061
    2 山东省高速养护集团有限公司, 济南 250032

通讯作者:

* 王冀鹏(1988—),男,汉族,河北邯郸人,博士,教授。研究方向:非饱和土力学的微宏观试验等。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
Number of
species
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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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