水力学

跨河桥梁基础冲刷研究综述

  • 王路 , 1 ,
  • 刘宏伟 1 ,
  • 魏凯 2 ,
  • Bruce MELVILLE 3 ,
  • 聂锐华 , 1
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  • 1 四川大学 山区河流保护与治理全国重点实验室,成都 610065
  • 2 西南交通大学 桥梁智能与绿色建造全国重点实验室,成都 611756
  • 3 Department of Civil and Environmental Engineering,University of Auckland,Auckland 1142,New Zealand
聂锐华(1978-),男,安徽岳西人,研究员,博士,研究方向为水力学及河流动力学。E-mail:

王路(1988-),男,四川蒲江人,研究员,博士,研究方向为水力学及河流动力学。E-mail:

Copy editor: 陈敏

收稿日期: 2024-05-26

  修回日期: 2024-09-02

  网络出版日期: 2025-01-02

基金资助

国家自然科学基金项目(52279074)

国家自然科学基金项目(U20A20319)

四川省科技计划项目(2023NSFSC1989)

Review of Research on Foundation Scour of River-Crossing Bridges

  • WANG Lu , 1 ,
  • LIU Hong-wei 1 ,
  • WEI Kai 2 ,
  • Bruce Melville 3 ,
  • NIE Rui-hua , 1
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  • 1 State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China
  • 2 State Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University, Chengdu 611756, China
  • 3 Department of Civil and Environmental Engineering, University of Auckland, Auckland 1142, New Zealand

Received date: 2024-05-26

  Revised date: 2024-09-02

  Online published: 2025-01-02

摘要

基础冲刷是导致跨河桥梁水毁的主要原因之一。归纳了跨河桥梁基础冲刷近60 a来的研究成果,总结了一般冲刷、束窄冲刷和局部冲刷3个方面的研究进展,并分析了现有研究的不足。过去60余年,国内外学者基于水槽试验、原型观测、数值模拟等方法,围绕跨河桥梁基础冲刷开展了大量研究,取得了一系列研究成果,显著提高了跨河桥梁基础冲刷的设计水平。由于已有跨河桥梁基础冲刷研究多局限于顺直河道、非黏性河床、单桩结构等简单边界条件,研究方法多基于水槽试验和特定桥梁的原型观测结果,较少考虑人类扰动对河床演变的影响,相关结论和设计方法的适用性和可靠性有限。未来研究需要更好地将水槽试验、原型观测、数值模拟、理论分析、人工神经网络、深度学习等方法进行融合,系统深入开展受人类扰动影响和复杂边界条件的跨河桥梁基础冲刷研究,完善跨河桥梁基础冲刷的理论体系,提出适用性更广、可靠性更高的冲刷设计方法。

本文引用格式

王路 , 刘宏伟 , 魏凯 , Bruce MELVILLE , 聂锐华 . 跨河桥梁基础冲刷研究综述[J]. 长江科学院院报, 2025 , 42(7) : 94 -103 . DOI: 10.11988/ckyyb.20240564

Abstract

Foundation scour is one of the primary causes of hydraulic failures in river-crossing bridges. By integrating flume experiments, prototype observations, numerical simulations, and artificial intelligence methods, this study reviews research on foundation scour of river-crossing bridges over the past six decades, summarizes progress in three aspects of general scour, contraction scour, and local scour, analyzes the limitations in existing research, and proposes future research directions. In terms of physical mechanisms, most existing studies focus on bridge foundation scour under simplified boundary conditions such as straight channels, non-cohesive riverbeds, and cylindrical structures. However, cohesive sediments prevalent in natural rivers exhibit complex force interactions and high randomness, resulting in scour processes for bridge foundations that differ significantly from those in non-cohesive riverbeds. Moreover, in common natural channels such as braided, branching, confluence, and alternating wide-narrow channels, water-sediment dynamics and riverbed evolution involve numerous factors with strong uncertainties, making scour mechanisms for bridge foundations more complex than those in straight channels. Therefore, future research must focus on scour mechanisms under more boundary conditions commonly found in natural rivers to improve the theoretical framework for foundation scour of river-crossing bridges. Regarding scour prediction methods, existing research primarily relies on flume experiments and prototype observations of specific bridges. The former’s prediction accuracy is severely affected by scale effects, while the latter has limited applicability. To date, there is a lack of predictive formulas or analytical models that quantitatively consider the scale effects on bridge foundation scour. Data-driven models such as artificial neural networks and deep learning can effectively compensate for the inability of conventional prediction methods for bridge foundation scour to account for complex boundary conditions. In particular, multi-module multilayer perceptrons (multi-module MLPs) can construct hybrid neural networks incorporating physical scour mechanisms, showing great potential in addressing the challenges of predicting scour under complex boundary conditions. In numerical modeling, existing methods are often applicable to low Reynolds number conditions, with insufficient accuracy in capturing turbulence at high Reynolds numbers and absence of standardized grid size criteria. Sediment transport is frequently computed using empirical formulas, and dynamic grid technologies often suffer from low precision. Existing numerical methods exhibit inadequate coupling between turbulence models and sediment transport models. Moreover, current numerical simulations are limited to non-cohesive riverbeds, with few models applicable to cohesive riverbeds and virtually no reported models suitable for stratified riverbeds. Therefore, numerical models for bridge foundation scour require in-depth investigation to address these issues in the future, improving their applicability and reliability under complex boundary conditions. In addition, intensified human interventions—including sand mining, channel regulation, and dam construction—have triggered rapid riverbed degradation in many rivers. These degradation events often occur at scales, rates, and complexity far beyond conventional understanding of general riverbed degradation, resulting in highly destructive and abrupt changes. Future research should systematically investigate riverbed evolution under human disturbances. To build a more comprehensive understanding of foundation scour of river-crossing bridges, future studies should better integrate flume experiments, prototype monitoring, numerical modeling, theoretical analysis, artificial neural networks, and deep learning methods. This will enable systematic investigation of bridge scour under human disturbance and complex boundary conditions, thereby improving the theoretical system and developing more widely applicable and reliable scour design methods.

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0 引言

我国是桥梁大国,截至2020年公路和铁路桥梁总数已超过100万座[1]。随着沿河经济带的快速发展,跨河桥梁逐渐成为主要的涉水交通基础设施。研究表明,水毁是跨河桥梁的主要损毁形式之一[2]:据统计,2007—2015年间我国受损毁的102座桥梁中有44座由水毁造成,占比高达43.1%[3]。基础冲刷作为跨河桥梁水毁的主要原因,是桥梁下部结构的重要设计参数,长期以来一直是国内外桥梁工程研究的重点[4]。近年来全球极端气候频率增加,进一步加大了跨河桥梁冲刷水毁的风险[5]
桥梁基础包含桥墩和桥台,其冲刷分为一般冲刷(general scour)、束窄冲刷(contraction scour)和局部冲刷(local scour):一般冲刷由河床演变(河床下切、弯道冲刷、交汇冲刷等)产生,与桥梁基础几何形态无关;束窄冲刷由河道自身缩窄或涉河建筑物修建减少过水面积、增加流速而产生;局部冲刷是桥梁基础改变其周围水流结构并与河床相互作用而产生(图1)[6]。根据桥梁上游河道水流是否达到床沙起动条件,局部冲刷可分为清水冲刷(clear-water scour,未达到起动条件)和浑水冲刷(live-bed scour,超过起动条件)[7]。需要注意的是,我国桥梁设计规范[8]将桥梁基础冲刷分为河床自然演变冲刷、一般冲刷和局部冲刷[8]。然而,由于国内外大多数桥梁基础冲刷研究基于一般冲刷、束窄冲刷和局部冲刷的分类体系,故本文后续内容表述中也将采用该分类体系。
图1 跨河桥梁基础冲刷类型示意图(参考Melville等[6]的研究)

Fig.1 Schematic diagram of foundation scour types for river-crossing bridges (after Melville et al[6])

跨河桥梁基础冲刷受水沙运动、河床演变、河道形态、地质条件、基础结构形态等多种因素影响,机理复杂、预测难度大,国内外学者对其进行了广泛的研究。最早关于跨河桥梁基础冲刷的系统研究可以追溯到20世纪50年代[9-10]。70年代后国内外学者采用水槽试验、原型观测、数值模拟、理论分析等方法,针对跨河桥梁基础一般冲刷、束窄冲刷和局部冲刷问题开展了大量研究并取得了一系列成果,显著提高了跨河桥梁基础冲刷的理论和设计水平。
然而,已有文献综述多聚焦桥梁基础局部冲刷,没有系统梳理和总结对桥梁基础安全同样重要的一般冲刷和束窄冲刷的研究成果。本文从一般冲刷、束窄冲刷、局部冲刷3个方面,系统梳理了过去60余年国内外跨河桥梁基础冲刷的研究进展,分析了已有研究在物理机制和设计方法方面的不足,提出了未来跨河桥梁基础冲刷的研究方向。

1 跨河桥梁基础冲刷研究进展

1.1 一般冲刷研究

一般冲刷由河流自身的河床演变产生,因此已有研究多从河床演变的角度开展。Lane[11]通过野外调查分析了推移质输沙率、床沙粒径、水流强度、河床坡度对河床演变的影响,提出了基于水流功率的河床下切预测方法。Galay[12]基于大量案例研究,发现侵蚀基面下降是导致河床下切的主要原因之一,进一步分析了侵蚀基面对河床演变的作用机制。Hickin等[13]基于野外观测资料,揭示了弯曲河道的河床演变规律,提出了弯道侧向侵蚀速率的计算方法。Melville等[6]基于前人数据,分析了交汇区的冲刷规律,发现交汇区冲刷深度随着交汇角和泥沙粒径的增大而增大。Guill等[14]基于水槽试验,研究了交汇角和干支流流量比对山区河流交汇区床面形态的影响。Sukhodolov等[15]通过野外观测研究了交汇区水流特性,分析了射流对交汇区河床局部冲刷的影响。Canelas等[16]基于水槽试验,分析了干支流流量比和支流泥沙补给对交汇区床面形态影响,探明了交汇区二次流形成和演化机制。Frings等[17]基于野外观测数据分析了莱茵河的河床下切过程,发现河道整治是造成莱茵河河床下切的主要原因之一。聂锐华等[18]基于案例分析,研究了强震受损山前河流的河床下切规律,提出了变化环境下山前河流河床下切的预测方法。Ma等[19]基于比尺模型试验,研究了侵蚀基面变化对上游河床演变的影响机制,发现侵蚀基面降低使上游河床发生下切和展宽。Yang等[20]通过原型观测分析了水库修建后下游河床的演变规律,发现水库下游河道有明显的主槽下切、滩地淤积特征。Guo等[21]基于案例分析,揭示了水库蓄水对下游河床和湖泊的影响规律。Calle等[22]基于GIS技术分析了采砂对地中海河流的影响,发现兰布拉河流受采砂影响河床下切3.5 m。Huang等[23]基于案例分析,发现中国台湾省八掌溪受人类活动和极端气候影响,河床最大下切约30 m,探明了堤坝等人工建筑对河床演变的影响机制。总体而言,目前关于自然演变河流中一般冲刷的理论研究相对成熟,而人类扰动下的一般冲刷研究尚以案例分析为主。

1.2 束窄冲刷研究

束窄冲刷分为水平和垂向束窄冲刷:水平束窄冲刷通常由河道自身变窄或修建涉河建筑物(桥台、桥墩、丁坝等)造成的过水面积减小、流速增加而产生;垂向束窄冲刷由桥面淹没引发的有压流产生[24]。由于垂向束窄冲刷与桥梁自身结构形态(桥面)有关,一些研究也将其归为局部冲刷[6],但目前主流观点仍倾向于将其归入束窄冲刷[24]
关于水平束窄冲刷研究最早可追溯到1934年,Straub[25]通过分析输沙平衡条件下长束窄河段(即束窄段长度大于其宽度)的冲刷规律,建立了长束窄河段冲刷深度的一维数学模型。此后的研究[26-27]进一步分析了输沙率、泥沙级配等对长束窄河段冲刷的影响,发展了Straub的长束窄河段冲刷模型。Briaud等[28]基于SRICOS-EFA方法研究了黏性河床束窄冲刷的历时变化过程,发现河道束窄程度和水流强度对冲刷深度有显著影响,连接角(宽窄过渡段与水流方向的夹角)主要影响最大冲刷深度发生的位置。Lai等[29]分析了二维数值模拟方法对束窄冲刷的适用性,建立了基于二维数值模型的束窄冲刷深度预测方法。Raikar等[30]基于人工神经网络、遗传算法,分析了束窄冲刷深度对不同参数的敏感性,发现河道束窄比对冲刷深度的影响最大,其次是床沙级配。
关于垂向束窄冲刷的研究起步较晚,Abed[31]基于水槽试验研究了有压流条件下的桥墩冲刷机理,发现有压流条件下的桥墩冲刷深度可达到自由表面流条件的2.3~10倍。Umbrell等[32]基于水槽试验分析了水流强度、桥面淹没度、床沙粒径对垂向束窄冲刷深度的影响,提出了垂向束窄冲刷深度的计算方法。Guo等[33]通过引入尾水深度的影响,将垂向束窄冲刷分为非淹没、部分淹没和完全淹没三类,并基于能量方程建立了预测垂向冲刷深度的新方法。Hahn等[34]通过水槽试验研究了水深、断面束窄程度、泥沙粒径、流速和冲刷时间对垂向束窄冲刷深度的影响,发现最大冲刷深度发生在束窄断面的下游。Guo[35]等基于水槽试验和理论分析,研究了垂向束窄冲刷深度的历时发展过程,提出了任一时刻垂向束窄冲刷深度的计算方法。Sturm等[24]结合水槽试验和前人数据,分析了水流强度对垂向束窄冲刷的影响,发现最大冲刷深度对应的水流强度接近泥沙起动条件,最大冲刷深度约为水深的0.45倍。Carnacina等[36]基于水槽试验,揭示了桥墩垂向束窄冲刷和局部冲刷的耦合机制,提出了有压流条件下桥墩冲刷深度的计算公式。Tang等[37]通过水槽试验研究了桥面淹没情况下垂向束窄冲刷、沙波运动与桥面升力之间相互作用机制,提出了淹没条件下桥面升力的表达式。整体上目前已构建了相对完善的束窄冲刷理论体系,已有一系列相对成熟的束窄冲刷计算方法。

1.3 局部冲刷研究

桥梁基础包含桥墩和桥台,其局部冲刷由桥梁基础结构与水流、河床相互作用产生。过去60余年,国内外学者从水流特性和冲刷形态2个方面围绕跨河桥梁基础的局部冲刷开展了大量研究。

1.3.1 桥墩冲刷区域水流特性

桥墩冲刷区域的流场是一个复杂的三维大尺度相干结构(图2),主要由三部分构成[6]:①水流在桥墩迎水面受压产生两股射流,向上的射流形成表面旋滚,向下的射流冲击河床;②向下射流与来流在床面耦合形成马蹄涡(horseshoe vortex);③水流从桥墩两侧发生边界层分离产生尾涡(wake vortex)。
图2 桥墩冲刷区域水流结构示意图(参考Melville等[6]的研究)

Fig.2 Schematic diagram of flow pattern in scour area of bridge pier (after Melville et al[6])

桥墩冲刷区域水流特性研究多基于水槽试验。Melville等[38]使用热膜风速仪测量了不同冲刷阶段圆柱体桥墩周围的流场,揭示了桥墩周围的水流演变特性及其与冲刷坑的相互作用机制。Dey等[39]采用声学多普勒流速仪测量了不同冲刷阶段桥墩上游冲刷坑内的流场,分析了马蹄涡的紊动特性。Guan等[40]采用粒子图像测速技术测量了不同冲刷阶段桥墩冲刷区域的流场,探明了清水冲刷条件下马蹄涡系统在冲刷坑中的发展规律。Kirkil等[41]基于数值模拟,探明了桥墩周围的流场演变特性,揭示了桥墩雷诺数对马蹄涡湍流系统的影响规律。

1.3.2 桥墩局部冲刷形态

桥墩冲刷形态研究从最简单的顺直河道、非黏性河床和单桩结构出发,通过分析不同变量对冲刷尺度的影响,建立相关量化关系或公式来指导冲刷设计。Breusers等[42]基于模型试验和野外观测数据,提出了桥墩冲刷深度的计算方法。Melville[43]基于水槽试验,揭示了桥墩的浑水冲刷机理,发现浑水冲刷深度的变化幅度与沙波陡度有关。Ettema等[44]研究了桥墩冲刷水槽试验的比尺效应,探明了桥墩宽度弗劳德数对冲刷深度的定量影响。Melville等[45]通过水槽试验分析了桥墩清水冲刷的时空演变规律,提出了桥墩清水冲刷深度历时发展过程的计算方法。Sheppard等[46]通过水槽试验分析了浑浊水流作用下桥墩的冲刷过程,发现水流浊度对桥墩冲刷速率与深度有显著影响。Lee等[47]基于水槽试验和前人数据,研究了床沙粗糙度对桥墩冲刷深度的影响,发现桥墩冲刷深度随无量纲床沙粒径先增加后减小。López等[48]通过水槽试验和数值模拟研究了非恒定流作用下桥墩的冲刷机理。Lança等[49]研究了水流雷诺数对桥墩冲刷深度的影响,发现桥墩冲刷深度随着水流黏度的增加而减小。祝志文等[50]分析了计算流体动力学在桥梁基础冲刷方面的运用,发现湍流模型对流动的非定常特性捕捉不足导致局部冲刷坑形态与试验不符。Wei等[51]基于水槽试验和数值模拟方法,研究了带台阶的大型桥墩的局部冲刷形态。
随着简单边界条件下的桥墩冲刷形态研究逐渐成熟,近年来国内外学者开始研究复杂边界条件下桥墩的冲刷形态。Yang等[52]通过水槽试验系统研究了复式桥墩的冲刷机理,提出了复式桥墩冲刷深度的计算方法。Yang等[53]通过水槽试验研究了排列方式、水流强度和泥沙粒径对桩群冲刷深度的定量影响。Pagliara等[54]通过水槽试验探明了漂浮物形状、厚度和宽度与桥墩达到最大冲刷深度所需时间之间的关系。Wang等[55]通过水槽试验揭示了桥墩与相邻矮堰的冲刷耦合机制,探明了两者间距对冲刷深度的影响规律。Ansari等[56]通过水槽试验研究了黏土河床中的桥墩冲刷机理,阐明了无黏性与黏土河床桥墩冲刷的差异。Yang等[57]基于混合神经网络预测复式桥墩平衡冲刷深度和冲刷历时演变。

1.3.3 桥台冲刷区域水流特性

桥台冲刷区域的流场结构和桥台长度相关。短桥台周围流场由3个部分组成:①桥台迎水面受压产生两股射流,向上的射流形成表面旋滚,向下的射流冲击河床;②向下射流与来流在床面耦合形成主涡(principal vortex);③桥台末端边界层分离形成尾涡(图3(a))。长桥台周围水流由4个部分组成[58]:①桥台上游靠近河岸区域形成了流速较缓的回流区;②由于相对水深较浅,桥台上游表面仅形成了向下射流;③向下射流与来流耦合形成主涡,主涡在桥台末端强烈的螺旋运动诱发了与其旋转方向相反的二次涡(secondary vortex);④桥台末端边界层分离形成尾涡(图3(b))。
图3 桥台冲刷区域水流结构示意图(参考Melville等[6]的研究)

Fig.3 Schematic diagram of flow pattern in scour area of bridge abutment (after Melville et al[6])

桥台冲刷区域的流场研究大多关注冲刷初始和平衡2个阶段。Kwan等[59]采用氢气泡示踪法测量了桥台冲刷区域的三维流场,发现桥台冲刷坑内的主涡和向下射流是造成桥台局部冲刷的主要原因。Chrisohoides等[58]通过数值模拟和水槽试验研究了冲刷初始阶段桥台周围的大尺度相干结构。Koken等[60]采用数值模拟方法研究了非淹没丁坝(与桥台几何形态相同)周围的湍流特性,发现主涡在时空上均呈现双峰振荡特征。

1.3.4 桥台局部冲刷形态

桥台局部冲刷形态研究以水槽试验为主,其研究思路与桥墩局部冲刷类似,即通过分析不同变量或参数对冲刷尺度的影响,建立相关量化关系或方程来指导冲刷设计。Melville[61]通过总结前人试验数据,探明了水深、流速、床沙粒径、桥台形状和河道类型对桥台局部冲刷深度的定量影响,提出了桥台局部冲刷深度的计算方法。Cardosohe等[62]、Coleman等[63]通过水槽试验研究了单一和复式河道中桥台的局部冲刷过程,探明了桥台长度对其局部冲刷深度历时发展的影响规律。Ballio等[64]通过水槽试验研究了桥台的浑水冲刷机理。Melville等[65]通过水槽试验研究了抛石防护设施长度对桥台冲刷的影响,探明了桥台沿水流方向长度对冲刷坑位置和深度的影响规律。Yang等[66]基于水槽试验研究了带抛石防护措施的桥台在复式河道中的冲刷过程,提出了带抛石防护措施桥台历时冲刷深度的计算方法。
综上所述,由于桥梁局部冲刷涉及基础结构与水流、河床之间的相互作用,边界条件多且机理复杂,相关研究成果也最为丰富。目前已经初步建立了桥梁基础局部冲刷的理论体系,提出了一系列局部冲刷预测方法。

1.4 跨河桥梁基础冲刷计算方法

跨河桥梁基础的埋深需要大于其总冲刷深度,因此总冲刷深度是跨河桥梁重要的设计参数。目前国内外普遍采用的设计思路是将一般冲刷、束窄冲刷和局部冲刷深度的总和作为桥梁基础的总冲刷深度[4,8];对于重大或重点桥梁工程需要采用比尺模型试验进行模拟预测。首先,根据河床演变类型(河床下切、弯道冲刷、交汇冲刷)选择对应的方法计算一般冲刷深度;然后,基于考虑一般冲刷深度的水力条件来计算束窄冲刷深度;最后,基于考虑一般冲刷和束窄冲刷深度的水力条件来计算局部冲刷深度,将3个部分冲刷深度相加得出总冲刷深度(图4)。
图4 总冲刷深度计算步骤 (参考Arneson等[4]的研究)

Fig.4 Calculation procedure for total scour depth (after Arneson et al[4])

表1总结了目前国内外常用的一般冲刷、束窄冲刷和局部冲刷深度的计算方法对应的参考文献。需要注意的是,上述跨河桥梁冲刷计算方法将一般冲刷、束窄冲刷和局部冲刷单独考虑,在计算时没有考虑不同类型冲刷之间的相互作用[24]。虽然近年来一些研究开始关注不同类型冲刷之间的相互耦合机制[24,36],但目前尚缺乏成熟的理论和设计方法,亟需开展系统深入研究。
表1 常用跨河桥梁冲刷深度计算方法

Table 1 Common calculation methods for scour depth at river-crossing bridges

一般冲刷深度 束窄冲刷深度 局部冲刷深度
横向 垂向 桥墩 桥台
Lacey[67]、Blench[68]、Hickin等[13]、Johnson等[69]、Maynord[70]、Melville等[6]、《公路工程水文勘测设计规范》(JTG C30—2015)[8] Laursen[26]、Gill[27]、《公路工程水文勘测设计规范》(JTG C30—2015)[8] Umbrell等[32]、Arneson等[4]、Sturm等[24] Melville等[6]、Coleaman[71]、Sheppard等[72]、Sheppard等[73]、《公路工程水文勘测设计规范》(JTG C30—2015)[8]、Moreno等[74] Froehlich[75]、Sturm[76]、Ettema[77]、《公路工程水文勘测设计规范》(JTG C30—2015)[8]、Sturm等[24]

2 研究不足与未来展望

过去60余年,国内外学者围绕跨河桥梁基础冲刷开展了大量的研究,取得了一系列研究成果,大幅提高了跨河桥梁基础的冲刷设计水平。然而,已有研究仍存在以下不足。

2.1 物理机制

在物理机制方面,已有研究多关注跨河桥梁基础在顺直河道、非黏性河床、柱体结构等简单边界条件下的冲刷。然而,天然河流中广泛存在的黏性沙受力复杂、运动随机性高[78],使得黏性沙河床中桥梁基础的冲刷过程较非黏性沙河床差异显著。另一方面,常见的分汊、辫状、交汇、宽窄相间等河道(图5)中水沙运动与河床演变涉及因子多、不确定性强,其中桥梁基础冲刷的机理较顺直河道更为复杂。此外,某些跨河桥梁出于结构安全方面的考虑常采用较单桩结构更为复杂的几何形态和布置方式,也大大增加了桥梁基础冲刷过程的复杂程度。由于目前对黏性河床、复杂形态河道、复杂布置形态等复杂边界条件下跨河桥梁基础冲刷机理缺乏清晰认识,严重制约了跨河桥梁基础冲刷的设计水平。因此,未来亟需研究更多天然河道中常见的边界条件下的跨河桥梁基础冲刷机理,进一步完善跨河桥梁基础冲刷的理论体系。
图5 辫状河段上修建的雅鲁藏布江特大桥(卫星图像来自Google地球)

Fig.5 Yarlung Tsangpo River Bridge built across braided river section (satellite image from Google Earth)

2.2 冲刷预测方法

在冲刷预测方法方面,已有研究多基于水槽试验和特定桥梁的原型观测结果,前者预测精度受比尺效应的影响严重[56],后者适用性有限。比尺效应是包括桥梁基础在内的涉河建筑物冲刷研究的经典难题[79],其产生的主要原因是基于相似原理并采用天然沙的水槽试验研究无法同时满足与原型的水流和泥沙运动相似(图6)。研究建筑物冲刷比尺效应的路径有3条:①通过不同尺度水槽试验和原型观测数据来定量揭示比尺效应对冲刷尺度的影响,修正已有预测公式并提高其精度和适用范围;②基于流体力学和泥沙运动力学等基础理论建立冲刷尺度的解析式;③通过建立可靠、高效率的数值方法,对原型尺度的冲刷过程进行模拟。迄今为止仍缺少考虑比尺效应对桥梁基础冲刷尺度定量影响的预测公式或解析模型。数据驱动模型(人工神经网络、深度学习等)可以较好地弥补传统桥墩基础冲刷预测方法无法考虑复杂边界条件影响的不足,尤其是多模块多层感知机(multi-module MLP)[57]可以在借鉴已有冲刷预测方法的基础上构建考虑桥梁基础冲刷物理机制的混合神经网络,在解决跨河桥梁基础冲刷预测难以考虑复杂边界条件问题上具有很大的潜力。因此,未来需要更好地结合室内水槽试验、原型观测、数值模拟、理论分析、人工神经网络、深度学习等方法,提出适用性更广、可靠性更高的跨河桥梁基础冲刷计算方法。
图6 跨河桥梁基础冲刷比尺效应

Fig.6 Scale effects of foundation scour of a river-crossing bridge

2.3 数值模拟

在数值模拟方面,已有方法多适用于低雷诺数条件,在高雷诺数条件下湍流捕捉精度不足,网格尺寸大小缺乏相应的标准[55]。泥沙输移计算多采用经验公式,动网格技术网格精度较低,已有数值模拟方法中湍流模型与泥沙输运模型耦合并不完善。另外,已有数值模拟方法仅适用于非黏性河床,难以适用于黏性河床,适用于分层河床的数值模型更是鲜见报道。因此,未来桥梁基础冲刷数值模型需要针对上述问题开展系统深入研究,提升数值模型在复杂边界条件下的适用性和可靠性。

2.4 人类活动影响

值得注意的是,近年来经济的飞速发展使得人类对河流的扰动加剧,受河床采砂、河道整治、高坝修建等人类活动影响,许多河流发生了河床急剧下切现象[80-81]。例如,2008年汶川地震后10 a间,沱江支流、岷江干流长达300 km的河段发生了严重河床下切,最大深度达27 m,造成包括S105省道石亭江大桥在内的30余座桥梁与拦河坝损毁(图7)[18];类似现象同样发生在四川省大渡河沙湾水电站下游段(2010—2019年河床整体下切近7 m)、台湾省八掌溪中游河段(1981—2012年河床最大下切约30 m)[23]、福建省闽江竹岐段(1994—2006年河床平均下切8 m、最大13.1 m)[82]、三峡水库下游宜枝河段河床平均下切3.5 m,最大下切深度16.4 m(宜都附近)等[83]。上述河床急剧下切尺度、速率和机理复杂程度远高于传统认知的一般性河床下切,具有更强的破坏性和突发性,大大增加了跨河桥梁基础一般冲刷的预测和防治难度,未来亟需针对人类扰动下的河床演变规律开展系统深入的研究。
图7 S105省道石亭江大桥河床急剧下切后桥墩完全裸露[18]

Fig.7 Full exposure of piers after severe riverbed degradation at Shiting River Bridge on Provincial Highway S105[18]

3 结束语

本文从一般冲刷、束窄冲刷、局部冲刷3个方面,归纳总结了国内外跨河桥梁基础冲刷的研究进展与不足。
过去60余年,国内外学者围绕跨河桥梁基础一般冲刷、束窄冲刷和局部冲刷开展了大量研究,提出了对应的冲刷深度计算方法,显著提升了跨河桥梁基础冲刷的理论和设计水平。
然而,已有跨河桥梁基础冲刷研究多局限于简单边界条件(如顺直河道、非黏性河床、单桩结构等),研究方法多采用水槽试验和原型观测,相关理论和设计方法较少考虑人类扰动对河床演变的影响,严重制约了其适用性和可靠性。未来研究在研究手段上需要更好地融合水槽试验、原型观测、数值模拟、理论分析、人工神经网络、深度学习等方法,在理论层面需要深入考虑复杂边界条件和人类活动的影响,进一步完善跨河桥梁基础冲刷的理论体系,提升冲刷设计方法的适用性和可靠性。
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