极端气候下交通基础设施脆弱性研究综述

贾宏宇; 肖楚照; 康炜; 王传琦; 郑史雄

doi:10.3969/j.issn.0258-2724.20230650

极端气候下交通基础设施脆弱性研究综述

doi: 10.3969/j.issn.0258-2724.20230650

贾宏宇^{1, 2,},
肖楚照¹,
康炜^{1, 3},
王传琦^{1, 4},
郑史雄^{1, 2, ,}

1.
西南交通大学土木工程学院，四川成都，610031
2.
西南交通大学桥梁智能与绿色建造全国重点实验室，四川成都，611756
3.
中铁第一勘察设计院集团有限公司，陕西西安，710043
4.
中国市政工程西南设计研究总院有限公司，四川成都，610031

基金项目: 国家自然科学基金项目（52178169）

详细信息

作者简介:
贾宏宇（1981—），男，副教授，博士生导师，研究方向为桥梁抗震，E-mail：Hongyu1016@swjtu.edu.cn

通讯作者:
郑史雄（1965—），男，教授，博士生导师，研究方向为桥梁抗风与抗震，E-mail：Zhengsx@swjtu.edu.cn

中图分类号: TU99；P429
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出版历程
- 收稿日期: 2023-12-06
- 录用日期: 2024-12-10
- 修回日期: 2024-01-15
- 网络出版日期: 2024-12-30

Review of Research on Vulnerability of Transportation Infrastructure to Extreme Climatic Conditions

JIA Hongyu^{1, 2
,},
XIAO Chuzhao¹,
KANG Wei^{1, 3},
WANG Chuanqi^{1, 4},
ZHENG Shixiong^{1, 2
, ,}

1.
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
2.
State Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University, Chengdu 611756, China
3.
China Railway First Survey and Design Institute Group Co., Ltd., Xi’an 710043, China
4.
Southwest Municipal Engineering Design & Research Institute of China, Chengdu 610031, China

摘要

摘要:
全球气候变化日益剧烈，极端强降水、高温、低温以及干旱等极端气候事件对现有交通基础设施的运行性能造成影响，甚至导致严重损坏. 与此同时，随着交通强国战略的深入实施，大量新的交通基础设施在恶劣环境中被建设，新建设施的功能性、耐久性和维护管理面临前所未有的挑战. 极端气候荷载变化迅速且难以预测，常常伴随多种灾害的耦合效应，使得交通基础设施在其作用下的破坏机理极为复杂. 为确保极端气候条件下交通基础设施的安全和效能，在国内外极端气候及多灾害耦合研究的基础上，系统梳理了极端气候的时空演变、多灾害耦合作用的研究历程以及多重灾害对工程结构的影响机理. 在此基础上，明确了极端气候影响的特性，并提出交通基础设施在设计、施工和维护阶段的防灾减灾设计原则. 同时，综合总结了在极端气候条件下交通基础设施的多灾害风险评估方法，并对未来的研究方向进行展望，指出利用人工智能和机器学习技术进行极端气候灾害的快速预测和评估，以及在全寿命周期内分析交通基础设施系统性能的变化将成为重要的发展趋势. 为桥梁、道路和隧道等交通基础设施在极端气候条件下的抗灾设计、性能评估和韧性提升提供了宝贵的参考.
- 极端气候 /
- 交通基础设施 /
- 多灾害 /
- 全寿命周期 /
- 抗震韧性
Abstract:
The intensifying global climate change is increasingly affecting the operational performance of existing transportation infrastructure due to extreme climatic events such as heavy precipitation, high temperatures, low temperatures, and drought, leading to severe damage. Meanwhile, with the further implementation of the strategy of building China with a strong transportation network, a significant number of new transportation infrastructure projects are being constructed in harsh environments, posing unprecedented challenges to the functionality, durability, and maintenance management of these new facilities. The characteristics of extreme climate loads include rapid and unpredictable variations, often accompanied by coupled effects of multiple disasters, rendering the mechanisms of damage to transportation infrastructure under their influence highly complex. To ensure the safety and effectiveness of transportation infrastructure under extreme climatic conditions, Chinese and international research on extreme climate and multi-disaster coupling was studied, and the research progress on spatiotemporal evolution of extreme climates and multi-disaster coupling effects was systematically reviewed. The impact mechanisms of multiple disasters on engineering structures were sorted out. Based on this foundation, the characteristics of extreme climate impacts were defined, and disaster prevention and reduction design principles for transportation infrastructure during the design, construction, and maintenance phases were proposed. Furthermore, methods for assessing multi-disaster risks to transportation infrastructure under extreme climatic conditions were comprehensively summarized, and future research was prospected, highlighting the importance of utilizing artificial intelligence and machine learning technologies for rapid prediction and assessment of extreme climatic disasters and analyzing changes in the performance of transportation infrastructure systems throughout their whole life cycle. This research provides valuable references for the disaster-resistant design, performance assessment, and resilience enhancement of transportation infrastructure such as bridges, roads, and tunnels under extreme climatic conditions.
- extreme climate /
- transportation infrastructure /
- multi-disaster /
- whole life cycle /
- seismic resilience

HTML全文

随着我国现代化步伐的加快，石油勘探、隧道施工、地热开发、矿业开采等地下工程变得日益重要. 无碳地热能在减少传统化石资源的消耗方面具有明显的优势，同时，煤层气地下气化、油页岩热解在减碳方面也显示出巨大潜力^[1-3]. 在这些工程应用中，岩石经历从常温到高温的演化过程，导致力学强度劣化，从而对围岩稳定带来了巨大的安全隐患. 考虑到围岩的长期稳定，需要解决岩石的热损伤问题，例如，在煤气化和油页岩热解储层，热裂纹会降低岩石的完整性，从而破坏岩层的整体结构. 因此，研究高温对岩石物理力学性能的影响具有重要意义.

近年来，国内外研究者对热处理岩石力学特性开展了大量研究. 研究表明，受温度作用的影响，岩石的物理力学特性会产生不同程度的劣化^[4-6]. 除了力学特性外，众多学者对岩石热损伤本构模型也开展了大量研究：李天斌等^[7]借助Weibull参数，基于Drucker-Prager准则建立了岩石损伤统计本构模型并定义了损伤变量；贾宝新等^[8]基于有效应力理论，借助Weibull分布函数，采用分段函数的方法建立了高温作用下岩石单轴压缩和三轴压缩的本构模型，结果表明，采用分段函数方法后的理论结果与室内试验曲线较接近.

由于受高温热损伤的作用，岩石内部的原生微裂隙和孔洞不断发育扩展，从经典弹塑性力学理论很难有效地判断强度变化和破坏行为. 能量存储与释放的过程从本质上能反映岩石内部损伤程度和裂纹发展的演变规律. 因此，基于热力学第一定律的能量法是构建热损伤岩石本构关系和探究岩石破坏行为的有效方法. Liu等^[9]基于能量耗散定义的损伤变量建立了能够准确描述岩石单轴压缩过程的损伤本构模型；Gong等^[10]基于单轴压缩下岩石的线性能量耗散规律，得出了基于能量耗散系数表征岩石损伤的方法；孙梦成等^[11]运用最小耗能原理和连续损伤理论构建了损伤本构模型，结果表明，该模型能较好地反映岩石的非线性力学行为.

综上所述，针对热处理砂岩在荷载作用下的能量演化规律和本构模型的研究取得了大量的成果^[12-16]. 但现有本构模型很少考虑初始压密阶段，压密阶段的力学行为对理解最终宏观破断机制起到了非常重要的作用. 本研究基于能量耗散理论深入分析热损伤砂岩的变形破裂过程，并对其进行阶段划分，构建考虑压密阶段的热-力耦合分段本构模型，并通过室内试验对模型可靠性进行验证.

1. 试验过程

1.1 试验方案

从施工现场取下一块完整砂岩，打包运至岩样加工室，严格按照国际岩石力学测试标准将试样加工成25 mm × 50 mm的标准圆柱体试样. 该马弗炉型号为FR-1236，马弗炉尺寸为540 mm × 550 mm × 415 mm，额定电压为220 V，处理温度分别为200、400、600、800 ℃和1000 ℃. 为确保砂岩试样受热均匀，马弗炉的加热速率设置为5 ℃/min. 当加热温度达到设定温度时，在马弗炉内保持该温度工况继续加热3 h后关闭电源，冷却至室温取出进行单轴压缩试验，每种工况至少准备3组平行试验. 试验装置为ISTRON万能材料试验机，该系统主要由控制面板、加载单元和数据采集单元组成，最大轴向荷载为250 kN，荷载测量精度为0.5%，位移测量精度为0.1%，加载系统采用位移控制，加载速率设置为0.05 mm/min.

1.2 试验结果

为探究不同温度热处理砂岩的贯通破裂模式和失效机制，通过对破裂后的试样进行筛选得到典型破裂模式图，如图1所示. 由图1可知：在热处理温度较低时，砂岩表观颜色为灰褐色，随着热处理温度的升高砂岩逐渐向红褐色转变；砂岩破裂模式由单一剪切破断向复杂的拉剪劈裂破坏转变. 例如，在常温下砂岩的破坏模式主要以剪切破坏为主，表现为脆性特征；当热处理温度增至200 ℃和400 ℃时，砂岩破坏模式呈现出“Y”型共轭张拉剪切混合破坏；当热处理温度在600～1000 ℃时，试样表观的裂纹由2条贯通式的“翼型”主裂纹和大量分支次裂纹组成，并伴随有局部脱落现象.

图 1 不同温度热处理典型砂岩破坏形态

Figure 1. Failure patterns of typical thermally-treated sandstone subjected to different temperatures

下载: 全尺寸图片幻灯片

不同温度热处理典型砂岩应力-应变曲线演化如图2所示. 随着热处理温度的升高，砂岩强度逐渐降低，曲线逐渐平缓，裂纹压密阶段在整个变形阶段的占比逐渐变大. 同时，对应峰后阶段的变形量也逐渐增大. 另外，从峰后应力-应变曲线的演化特征可知，当热处理温度达到400 ℃时，砂岩的延性逐渐增加，出现这种现象的原因：一方面由于分子间热运动能力增强，导致砂岩内部矿物颗粒间的黏聚力减弱，颗粒间更易滑动；另一方面，引起砂岩中高岭石矿物分解的温度为400 ℃，高岭石矿物的分解导致硅酸盐晶体重新排列，从而提高了砂岩的塑性性能.

图 2 不同温度热处理典型砂岩应力-应变曲线

Figure 2. Stress–strain curves for typical thermally-treated sandstone subjected to different temperatures

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通过对不同温度作用下砂岩抗压强度和弹性模量提取计算，得到不同热处理温度下砂岩力学参量演化规律，如图3所示.

图 3 不同温度作用砂岩力学参数变化规律

Figure 3. Variation pattern of mechanical parameters for sandstone subjected to different temperatures

下载: 全尺寸图片幻灯片

从图3可以看出：砂岩的峰值应力和弹性模量均随着温度的升高先上升后下降；当热处理温度低于200 ℃时，砂岩强度呈微小上升趋势，主要原因为试样内的水分被蒸发致使矿物颗粒之间形成塑性扩张且增加了基质之间的内摩擦作用；当热处理温度大于200 ℃时，峰值应力和弹性模量逐渐减小，由于经过高温处理后，砂岩内部矿物成分发生了化学反应，其热膨胀现象更加明显，导致内部微裂纹数量显著增加；当热处理温度大于600 ℃时，石英等矿物在高温下形成新的晶体结构，矿物之间的晶间裂纹和穿晶裂纹密度急剧增加；热应力作用致使微裂纹扩展、延伸，这一过程也改变砂岩的孔隙结构和连通性，导致其孔隙度增加，最终导致砂岩力学性能劣化.

2. 热处理砂岩能量演化机制

2.1 能量耗散原理

物质破坏的本质是其内部耗散能与弹性能演化的过程，从能量角度出发可以更好地解释岩石变形破坏过程. 根据热力学第一定律，一个热力系统内部能量增减等于外界传递的热量和所做功的总和^[17]. 假定在加载过程中系统与外界没有能量交换，试验机对岩石做的功全部转换为弹性能和耗散能. 在单轴压缩试验中，试样总能量 $U$ 与弹性能 ${U_{\mathrm{e}}}$ 、耗散能 ${U_{\mathrm{d}}}$ 的关系为

$U = {U_{\mathrm{d}}} + {U_{\mathrm{e}}} .$

(1)

总能量计算公式为

$U = \int_0^\varepsilon {\sigma {\mathrm{d}}\varepsilon } \text{，}$

(2)

式中： $\varepsilon$ 为轴向应变， $\sigma$ 为轴向应力.

弹性应变能计算公式简化为

${U_{\mathrm{e}}} = \frac{{{\sigma ^2}}}{{2{E_{}}}} \text{，}$

(3)

式中： $E$ 为弹性模量.

耗散能计算公式为

${U_{\mathrm{d}}} = U - {U_{\mathrm{e}}} = \int_0^\varepsilon \sigma {\mathrm{d}}\varepsilon - \frac{{{\sigma ^2}}}{{2E}} .$

(4)

2.2 不同温度作用下砂岩能量演化规律

为了进一步探究不同温度热处理作用下砂岩变形破坏机制，基于式（1）～（4）计算加载过程中的总能量、弹性应变能和耗散能，将其绘制成曲线，如图4所示.

图 4 不同温度热处理试样能量演化曲线

Figure 4. Energy evolution of thermally-treated sandstone subjected to different temperatures

下载: 全尺寸图片幻灯片

基于耗散能演化规律将岩石变形破坏分为微裂纹闭合阶段、弹性阶段、宏观裂纹扩展阶段和峰后阶段：在第一加载阶段即微裂纹闭合阶段，由于加载初期砂岩内部发育有大量微裂纹，在外荷载作用下微裂纹逐渐闭合，晶体结构的变形以及矿物颗粒之间的摩擦作用，这些变化均伴随着能量的消耗，耗散能曲线缓慢上升，该阶段输入的机械能主要以弹性能的形式存储于试样内；在弹性阶段，外力做功几乎全部以弹性能的形式存储于试样内，耗散能基本不变，在此阶段随着荷载的增加试样内无明显的裂纹萌生；在裂纹扩展阶段，耗散能逐渐增加，演化速率逐渐变大，耗散能曲线近似呈凹型演变，弹性能增速逐渐趋近于0，该曲线由凹型逐渐向凸型演变，此时产生的耗散能增加，主要原因为试样内部产生大量裂纹而导致能量消耗增加；峰后阶段弹性能得到释放，弹性能曲线陡然下降，耗散能急剧上升，试样内部裂纹相互贯通形成宏观裂纹，试样逐渐失去承载能力.

2.3 不同温度作用下砂岩弹性能耗比

弹-塑性转变点标志着砂岩从形状能够恢复的弹性变形向产生永久形变的塑性变形转变，这一转变在理解材料的力学响应和结构完整性方面至关重要. 砂岩作为典型的非均质材料，加载过程中的变形破坏行为极其复杂. 弹性能耗比K即耗散能与弹性能之比，可以在一定程度上反映砂岩能量储存的大小，如式（5）.

$K = \frac{{{U_{\mathrm{d}}}}}{{{U_{\mathrm{e}}}}}.$

(5)

在砂岩受载过程中，外力对其做功大部分以弹性能的形式储存于砂岩中，小部分则由于内部颗粒的摩擦和变形以热量的形式消耗. 当试样内裂隙发展到一定程度时便会贯通破裂，破坏后岩样内部的能量释放，并破裂成多个小的基质颗粒再次进入新的稳定状态. 因此，弹性能耗比的突变可作为岩样由弹性向塑性转变的临界点.

图5给出了3种典型温度试样弹性能耗比演化规律，由于在加载前期能量变化较小，误差较大，故从应变值为0.002处开始计算. 在加载前期，弹性能耗散比逐渐变小，随后进入弹性阶段，外界输入能量主要以弹性能储存于砂岩中，该阶段弹性能耗比变化平稳；随着荷载的增加，弹性能耗比再次上升；当弹性能耗比达到最小值时即弹性能达到最大，此时岩样内部损伤达到最大，介于稳定状态向不稳定状态转换的临界点，该临界点可作为岩石由弹性向塑性转变的突变点.

图 5 典型温度作用下砂岩弹性能耗散比曲线

Figure 5. Elastic energy dissipation ratio of sandstone subjected to typical temperatures

下载: 全尺寸图片幻灯片

通过对比常温、600 ℃和1000 ℃ 3种典型温度工况下试样的最小弹性能耗比发现：1）突变点对应的应力与峰值应力比值逐渐变小，该结论也进一步证实了随着温度增加，试样的延性逐渐增大. 2）另外，砂岩破裂后最终的K值在600 ℃和1000 ℃时均有所提升，并且600 ℃时增幅大于1000 ℃，由于砂岩中的石英矿物在573 ℃时发生了α—β相变转化，导致砂岩热膨胀系数变大，热缺陷程度显著增加，致使600 ℃以后热损伤大幅增加. 该现象的主要原因是在热应力作用下，砂岩内部会产生大量微观裂纹，碳酸盐的分解和热应力作用导致砂岩内部孔隙、裂纹数量急剧增大，砂岩内部空间结构变大. 在1000 ℃时，碳酸钙分解为二氧化碳和氧化钙，由于碳酸钙分解导致体积和孔隙结构产生变化，致使热损伤增幅有所减缓.

3. 热-力耦合本构模型

3.1 损伤变量

随着热处理温度的升高，砂岩内部会产生大量的细观裂纹，使得砂岩的弹性模量逐渐降低，岩石产生损伤. 故通常采用相对弹性模量来定义温度为t时的热损伤变量^[18-19]，如式（6）.

${D_t} = 1 - \frac{{{E_t}}}{{{E_0}}},$

(6)

式中： ${E_0}$ 为常温下砂岩的弹性模量， ${E_t}$ 为温度t 作用后砂岩的弹性模量.

由耗散能定义的热损伤变量为

${D_t} = 1 - \alpha {\left( {\frac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)^\beta },$

(7)

式中： ${U_{{\mathrm{d}}0}}$ 为常温下砂岩峰值耗散能； ${U_{{\mathrm{d}}t}}$ 为温度t ℃作用后砂岩峰值耗散能； $\alpha$ 、 $\beta$ 为拟合参数，根据砂岩的具体特性（成分、结构和预处理条件等）进行确定，以确保模型能够精确描述不同温度对砂岩损伤演化的影响.

通过对式（6）、（7）拟合得到 $\alpha$ =0.99， $\beta$ =1.05，其拟合度R²=0.99.

3.2 荷载损伤变量

由于岩石类材料自身发育有大量初始缺陷，故通常把岩石材料视为各向异性材料. 在外力作用下，砂岩内部裂纹经历了一系列发育成核、萌生扩展和贯通失效过程. 由于整个变形破坏过程具有随机性，故采用Weibull分布函数表征砂岩的微元强度，如式（8）.

$\varphi (x) = \frac{n}{m}{\left(\frac{x}{m}\right)^{^{n - 1}}}{\mathrm{exp}}\left( { - {{\left( {\frac{x}{m}} \right)}^n}} \right),$

(8)

式中：x为微元体强度，m为微元体尺寸参数，n为微元体形状参数.

基于文献[20]的损伤参量与分布密度函数之间的关系可得

$\varphi (\varepsilon ) = \frac{{{\mathrm{d}}D}}{{{\mathrm{d}}\varepsilon }},$

(9)

式中：D为损伤变量.

对式（9）进行积分得

${D_{{f}}} = \int_0^\varepsilon {\varphi (x)} {\mathrm{d}}x = 1 - {\mathrm{exp}}\left( { - {{\left( {\frac{\varepsilon }{m}} \right)}^n}} \right),$

(10)

式中： ${D_{{f}}}$ 为荷载f作用时砂岩的损伤变量.

3.3 热-力耦合损伤本构模型

为了描述不同温度热处理砂岩的损伤本构关系，将高温处理视为砂岩的第一损伤状态，受荷过程视为其第二损伤状态. 根据Lemaitre应变等价假说，温度与荷载耦合作用的损伤变量计算公式为

$1 - {D_{t - f}} = (1 - {D_t})(1 - {D_f}),$

(11)

式中： ${D_{t - f}}$ 为耦合损伤变量.

将式（7）和式（10）代入式（11）中可得耦合损伤变量为

${D_{t - f}} = 1 - \alpha {\left( {\frac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)^\beta }\exp \left( { - {{\left( {\frac{x}{m}} \right)}^n}} \right).$

(12)

在加载初期存在着明显的裂纹闭合现象，随着温度的升高，此现象愈加明显. 传统损伤本构模型得到的理论曲线与试验曲线相比，其峰前吻合度较低，故采用分段方法构建热-力耦合本构模型，即以裂纹闭合段结束，弹性段开始点为分界点. 在分界点前砂岩内部孔隙逐渐闭合，岩石内部裂隙并无扩展的迹象且不产生损伤. 损伤变量为

$D = \left\{ {\begin{array}{*{20}{l}} {1 - \alpha {{\left( {\dfrac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)}^\beta },\quad\varepsilon \lt {\varepsilon _{\mathrm{c}}}}, \\ {1 - \alpha {{\left( {\dfrac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)}^\beta }{\mathrm{exp}}\left( { - {{\left( {\dfrac{{\varepsilon - {\varepsilon _{\mathrm{c}}}}}{m}} \right)}^n}} \right),\quad\varepsilon \gt {\varepsilon _{\mathrm{c}}}} , \end{array}} \right.$

(13)

式中： $\varepsilon_{{\mathrm{c}}}$ 为裂纹闭合段结束时的应变.

由于在裂纹闭合阶段砂岩主要以孔洞、微裂纹的压密为主，考虑到该阶段砂岩内部微观结构的变化，Weibull分布函数可以更好地反演微观缺陷在受力下的损伤情况，故裂纹闭合阶段本构模型为

$\sigma = {E_0}\varepsilon \alpha {\left( {\frac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}o}}}}} \right)^\beta }\left\{ {1 - \exp \left( { - {{\left( {\frac{\varepsilon }{m}} \right)}^n}} \right)} \right\}.$

(14)

随着作用力的增加，砂岩内部裂纹发育扩展，外荷载对砂岩造成损伤. 此阶段采用综合损伤变量，结合损伤力学的基本关系得

$\sigma = E(1 - D)\varepsilon = {E_0}\varepsilon {\left( {\alpha {{\left( {\frac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)}^\beta }} \right)^2}\exp \left( { - {{\left( {\frac{\varepsilon }{m}} \right)}^n}} \right).$

(15)

结合式（14）和式（15），热损伤砂岩本构模型为

$\sigma = \left\{ {\begin{array}{*{20}{l}} {E_0}\varepsilon \alpha {{\left( {\dfrac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)}^\beta }\left( {1 - {\mathrm{exp}}\left( { - {{\left( {\dfrac{\varepsilon }{{{m_1}}}} \right)}^{{n_1}}}} \right)} \right),\\ \quad\varepsilon \leqslant {\varepsilon _{\mathrm{c}}} ,\\ {E_0}\left( {\varepsilon - {\varepsilon _{\mathrm{c}}}} \right){{\left( {\alpha {{\left( {\dfrac{{{U_{{\mathrm{d}}t}}}}{{{U_{{\mathrm{d}}0}}}}} \right)}^\beta }} \right)}^2}{\mathrm{exp}}\left( { - {{\left( {\dfrac{{\varepsilon - {\varepsilon _{\mathrm{c}}}}}{{{m_2}}}} \right)}^{{n_2}}}} \right) + {\sigma _{\mathrm{c}}},\\ \quad\varepsilon \gt {\varepsilon _{\mathrm{c}}} , \end{array}} \right.$

(16)

式中： ${\sigma _{\mathrm{c}}}$ 裂纹闭合段结束时的应力， ${m_1}$ 和 ${n_1}$ 为裂纹闭合段的尺寸参数和形状参数， ${m_2}$ 和 ${n_2}$ 为压密段结束后的尺寸参数和形状参数.

4. 损伤本构模型验证

不同温度作用下损伤变量方程中参数m、n的演化规律，如图6所示. 尺寸参数m为Weibull分布函数中尺度参数；形状参数n为材料的均质性程度指标，n值较高表明岩石材料的力学特性均质性程度较高^[21]. 由图6可知： m整体呈现出与砂岩强度变化一致的规律，随热处理温度升高先上升后下降，在200 ℃时峰值应力最大，对应m值也增至最大； n随着热处理温度的升高逐渐降低，这是由于n在一定程度上可以反映岩石的塑性特性，随着热处理温度升高砂岩塑性特征逐渐显著.

图 6 本构模型拟合参数变化规律

Figure 6. Variation pattern of fitting parameters for constitutive model

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由式（16）计算得到不同温度热处理砂岩应力−应变的理论曲线与试验曲线如图7所示. 通过图7可知：理论曲线与试验曲线吻合度较高，本文构建的热−力损伤本构模型能够反映不同热损伤工况下砂岩变形破坏的演化过程. 需要说明的是，该方法构建的理论模型也存在一定的缺陷，比如，在分段点处，理论曲线存在间断点. 尽管不足，但理论曲线的力学演化规律与室内试验结果较一致，表明基于能耗方法表征热损伤具有一定的合理性和可行性.

图 7 不同温度热处理砂岩室内试验-理论模型对比曲线

Figure 7. Comparison curves of laboratory test and theoretical model for sandstone subjected to different temperatures

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5. 结　论

1）随着温度增加，热处理砂岩的峰值应力和弹性模量先增加后降低，脆-延性转变的临界阈值温度为200 ℃，破断模式由斜向剪切裂破坏向“Y”型共轭拉剪切混合破坏转变.

2）基于能量法将整个加载过程分为微裂纹闭合阶段、弹性阶段、宏观裂纹扩展阶段和峰后阶段：在裂纹闭合阶段微裂隙、孔洞受压闭合，耗散能缓慢上升；弹性阶段耗散能保持不变，弹性能逐渐增加；裂纹闭合段耗散能和弹性能均逐渐增加，峰后阶段耗散能急剧上升，弹性能迅速下降.

3）弹性能耗比最小值是砂岩整体状态由稳定向不稳定转变的阈值，耗散能演变曲线斜率由负向正转变的突变点可作为岩石由弹性向塑性转变的临界点.

4）基于构建的热-力耦合损伤变量建立了以裂纹闭合点为分段点的损伤本构模型，模型中Weibull参数在一定程度上可以反映砂岩的强度和塑性特征，理论结果与室内试验结果较一致，该模型能够量化热-力耦合作用下砂岩变形破裂全过程.

致谢：桥梁无损检测与工程计算四川省高校重点实验室开放课题基金（2022QZJ01）.

图 1 长江流域极端气候事件危险性等级（198l—2010年）^[5]

Figure 1. Risk level of extreme climatic events in Yangtze River Basin （198l–2010）^[5]

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图 2 极端气候对交通基础设施的影响

Figure 2. Impacts of extreme climates on transportation infrastructure

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图 3 长江流域极端气候事件年变化率（196l—2020年）^[5]

Figure 3. Annual change rate of extreme climatic events in Yangtze River Basin （1961–2020）^[5]

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图 4 缺陷桥梁适应气候变化的成本

Figure 4. Cost of climate change adaptation for defective bridges

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图 5 极端气候事件引起的生命损失

Figure 5. Loss of life due to extreme climatic events

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图 6 暴雨导致Hatchie River 桥梁冲刷破坏

Figure 6. Erosion damage to Hatchie River Bridge caused by heavy rain

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图 7 飓风桑迪引起公路和桥梁破坏

Figure 7. Damage to roads and bridges caused by hurricane Sandy

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图 8 特大暴雨引起石太铁路桥梁垮塌

Figure 8. Collapse of Shijiazhuang-Taiyuan Railway Bridge caused by heavy rain

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图 9 多灾害风险矩阵

Figure 9. Multi-disaster risk matrix

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图 10 台风灾害桥梁设计风险矩阵

Figure 10. Risk matrix of bridge design in typhoon disaster

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图 11 极端气候灾害时空分布

Figure 11. Spatiotemporal distribution of extreme climatic disasters

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图 12 气候多灾害评估量化步骤

Figure 12. Quantitative steps of climatic multi-disaster assessment

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图 13 冲刷主动防护措施^[79]

Figure 13. Active protection measures for erosion^[79]

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图 14 冲刷被动防护措施^[79]

Figure 14. Passive protection measures for erosion^[79]

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图 15 基于时变风险模型的概率密度函数与风险重现区间的关系^[54]

Figure 15. Relationship between probability density function and risk recurrence interval based on time-varying risk model^[54]

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图 16 全寿命周期内性能预测

Figure 16. Performance prediction during whole life cycle

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图 17 最优Copula函数步骤

Figure 17. Steps for optimal Copula function

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图 18 风险曲线主要流程

Figure 18. Main process of risk curve calculation

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图 19 风险评估框架主要流程

Figure 19. Main process of risk assessment framework

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图 20 技术路线

Figure 20. Technology roadmap

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图 21 中国典型灾害地区分布^[67]

Figure 21. Distribution of typical disaster areas in China^[67]

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表 1 未来中国年平均地表气温与降水量（相对1961—1990年平均值）

Table 1. Annual average surface temperature and precipitation in China in the future （relative to average value in 1961–1990）

年份温度变化/℃ 降水变化%

2020 年 1.3～2.1 2～3

2030 年 1.5～2.8

2050 年 2.3～3.3 5～7

2100 年 3.9～6.0 11～17

下载: 导出CSV

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