Research Progress on Disaster-Causing Mechanisms and Monitoring Assessment of Flood Impact and Scour on Bridges
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摘要:
随着极端暴雨和洪水事件频发,桥梁因洪冲导致的水毁已成为威胁其安全运营的首要因素之一. 本文围绕桥梁洪冲致灾全过程,重点探讨和系统综述了冲刷发展机理、结构动力响应、智能监测预警及综合风险评估4个方面的研究进展. 从水文条件、结构参数与泥沙特性3个维度,分析桥梁基础局部冲刷的物理机制与演化规律的研究;阐述水动力荷载与基础冲刷耦合作用下,桥梁上部结构、墩台及基础体系的动力响应特征与典型失效模式;在监测预警方面,综述了基于声、光、电、力等原理的监测方法,并着重分析数据驱动与人工智能模型在冲刷深度预测中的应用潜力与当前局限;在风险评估层面,梳理从传统确定性分析向概率性易损性及系统韧性评估的范式演进;基于现有研究的不足,展望了未来的关键研究方向,包括复杂非恒定水文与波流耦合条件下的冲刷机理、多灾害链作用下的结构系统性能演化、多源信息融合的洪冲下桥梁智能感知与动态预警以及面向全生命周期的风险与韧性评估框架的构建. 可为桥梁抗洪冲韧性提升的理论研究与工程实践提供参考.
Abstract:With the frequent occurrence of extreme rainstorms and flood events, water damage of bridges induced by flood impact and scour has become one of the primary factors threatening safe operation. The entire disaster-causing process of bridges induced by flood impact and scour was studied, and the research progress in four aspects, namely scour development mechanisms, structural dynamic responses, intelligent monitoring and early warning, and comprehensive risk assessment, was emphatically discussed and systematically reviewed. From three dimensions of hydrological conditions, structural parameters, and sediment characteristics, the research on the physical mechanisms and evolution laws of local scour around bridge foundations was analyzed. Under the coupling action of hydrodynamic loads and foundation scour, the dynamic response characteristics and typical failure modes of the bridge superstructure, piers and abutments, and foundation system were elucidated. In terms of monitoring and early warning, the monitoring methods based on acoustic, optical, electrical, and mechanical principles were reviewed, and the application potential and current limitations of data-driven and artificial intelligence models in scour depth prediction were emphatically analyzed. At the level of risk assessment, the paradigm evolution from traditional deterministic analysis to probabilistic vulnerability and systemic resilience evaluation was systematically summarized. Based on the shortcomings of existing research, key future research directions were identified, including the scour mechanisms under complex unsteady hydrology and wave-current coupling conditions, the performance evolution of structural systems under the action of multiple disaster chains, the intelligent perception and dynamic early warning of bridges under flood impact and scour based on multi-source information fusion, and the construction of risk and resilience assessment frameworks toward the whole life cycle. Reference can be provided for theoretical research and engineering practice aimed at enhancing the flood impact and scour resilience of bridges.
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表 1 波流作用下平衡冲刷深度公式对比[16]
Table 1. Comparison of equilibrium scour depth formulas under wave-current action[16]
学者 平衡冲刷深度公式 公式特点 Sumer 等 $ \dfrac{S}{D}=1.3\left(1-\exp\left(-0.03\left(KC-6\right)\right)\right)\text{,}\quad KC\geqslant6,(1) $ 适用于波浪作用强烈的情况,精度较高,但对于较弱波流环境可能不够准确 Dogan $ \dfrac{S}{D}=1.3\left(1-\exp\left(-0.0\text{22}\left(KC-\text{4}\right)\right)\right),\quad KC\geqslant\text{4},(2) $ 适用于较低强度的波流环境. 在中等波流强度下表现良好,但可能无法适应极端波浪情况 $ \dfrac{S}{D}=\text{0.003 7}\dfrac{K{C}^{2/3}}{\sqrt{D/\lambda }},(3) $ 结合了 KC 数与桥梁几何尺寸的关系,适用于桥梁几何尺寸较为简单的环境 Raaijmakers 等 $ \dfrac{S}{D}=1.5\tanh \dfrac{h}{D} {K}_{\text{w}}{K}_{\text{h}} ,(4)$ 考虑了水深与冲刷深度的非线性关系,适用于多变水文条件 注:S 为冲刷深度,D 为桩基直径,h 为水深,Kw 为波浪作用的修正因子,Kh 为桩高修正系数,λ 为波长. 表 2 洪水作用下桥梁破坏形式[41]
Table 2. Failure forms of bridge under flood action
失效结构 破坏结构 受力形式 上部结构
破坏剪切破坏 竖向力 滑动破坏 水平力 梁体倾覆 水平力、动水压力
竖向分量桥墩破坏 墩顶水平位移过大
导致倾斜水平力、冲刷作用 偏向过大导致倾覆 弯剪开裂 漂浮物撞击 基础破坏 基础底面滑移 水平力、竖向力、
冲刷作用地基塑性形变 局部压力过高 地基瞬时液化 向上孔隙水压力增大 规范名称 AASHTO LRFD 桥梁设计规范 公路桥涵设计
通用规范AS5100 桥梁
设计规范公式 $ P=\dfrac{{C}_{\text{D}}\gamma {V}^{2}}{2g} $ $ F_{\mathrm{w}}=\dfrac{C_{\text{D}}A\gamma V^2}{2g} $ $ F\mathrm{_w}=\dfrac{C_{\text{D}}\rho V^2A}{2} $ 方法 花费/美元 精度 耐久性 安装 优缺点 目视检测法 500~ 1000 低 难以测量洪峰冲刷深度,精度取决于工作人员 力学原理监测方法 3000 中 差 简单 原理简单,难以监测回填过程 电磁原理监测方法 2000 ~10000 高 中、高 简单 测量精度高,容易受外界磁场干扰 声波监测方法 5~ 15000 高 中 简单 简单精度高,精度受外界环境干扰 光栅光纤传感器 5000 ~10000 高 中 较难 精度高,价格相对较高,多用于实验室 表 5 近年不同预测冲刷的人工智能模型和算法对比
Table 5. Comparison of different artificial intelligence models and algorithms for predicting scour in recent years
学者 模型 结构 输入特征 Ahmadianfar 等[92] 最小二乘法结合高斯过程归、随机森林模型 非均匀间距群桩 水文特征:水深、平均流速、临界流速
结构特征:桩径、流向桩间距、横向桩间距、流向桩个数、横向桩个数
土体特征:泥沙中值粒径Marulasiddappa 等[86] 自适应模糊推理系统、极端梯度树提升、数据处理群体法、多元自适应回归样条 桥台 水文特征:平均流速、水深
结构特征:桥台长度、宽度
土体特征:泥沙粒径Kim 等[87] 极端梯度提升和沙普利加性解释算法 桥墩 水文特征:水深、流速、泥沙启动流速
结构特征:桥墩宽度
土体特征:泥沙中值粒径Nandi 等[93] 分类增强、堆叠回归器 桥墩 水文特征:流量强度、水深、弗劳德数、雷诺数
结构特征:收缩比
土体特征:粗细、粒度组成Choi 等[94] 自适应模糊推理系统、人工神经网络 桥墩 水文特征:平均流速、水深、临界流速
结构特征:桥墩宽度
土体特征:泥沙粒径Feng 等[88] 支持向量机 桥墩 结构特征:桩尺寸、桩型、桩帽厚度、墩尺寸、频率
土体特征:密度、密实度Chen 等[89] 物理信息神经网络 单桩 结构特征:结构尺寸、频率
土体特征:弹性模量、密实度、重度、内摩擦角Guo 等[91] 自适应模糊推理系统 单桩 结构特征:频率变化率、曲率、曲差 -
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