Multiscale and probabilistic modelling of progressive slope failure

渐进式边坡破坏的多尺度和概率建模

• 批准号: EP/V028723/1
• 负责人: Tao Zhao
• 金额: $ 33.9万
• 依托单位: Brunel University London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV028723%2F1
• 关键词: Multiscale; probabilistic; modelling; progressive; slope

In the UK and globally, the slope failures of various sizes are crucially affecting the sustainable development of resilient cities, as its occurrence can significantly threaten the populations, infrastructures, public services, and environment. For example, the British Geological Survey has estimated that 10% of slopes in the UK are classified as at moderate to significant landslide risk, with more than 7% of the main transport networks located in these areas. These slopes may fail during prolonged periods of wet weather or more intensive short duration rainfall events. To date, the public awareness of slope failure risk is high, but our understanding of its fundamental failure mechanism and countermeasures are still very limited. This is mainly due to the difficulties in analysing the multiscale responses and characterize the spatial inhomogeneity of material properties of slopes. Laboratory and numerical investigations with well-developed empirical models can explain the general features of some specific slope failure events but cannot be applied universally. Some challenging issues need to be addressed, such as i) How to develop reliable mathematical models with multiscale modelling capability to analyse the progressive failure of slopes? ii) How to address the spatial variabilities and uncertainties of real slopes, e.g. material property, fractures, fluid permeability? iii) How to accurately estimate the spreading of landslide and its impact on infrastructures? The fundamental scientific issue of these challenges is the weakening mechanism of inhomogeneous slopes at different scales as it determines the slope responses under various geological and environmental conditions.The proposed research aims to explore the fundamental mechanism of progressive slope failure and its impacts on infrastructures via a multiscale and probabilistic modelling approach. It enables the large deformation of slopes to be conveniently analysed by FEM as boundary value problem (BVP), while the local fracturing, cracking, or discontinuous behaviours of soil to be evaluated in smaller discrete subdomains through granular mechanics by DEM. The boundary condition of DEM assembly is derived from the global deformation of FEM meshes. In the analysis, the soil/rock properties (e.g. elastic modulus, friction coefficient, strength, and fluid permeability) will be evaluated as random fields with spatial variabilities. The numerical modelling can effectively bridge the gap between the microscopic material properties and the overall macroscopic slope responses. In the numerical modelling, the contributions of material inhomogeneity and discontinuity to slope failure and subsequence landslide spreading can be effectively investigated. The internal fracture would occur naturally when the loading stress exceeds the particle bonding strength at the microscale, which avoids the use of some phenomenological constitutive laws in conventional continuum modelling. As a multidisciplinary research, this project will involve the subjects of geotechnical engineering, computational geotechnics, geology, statistics, soil/rock mechanics and granular mechanics. The proposed numerical model will benefit all researchers and stakeholders in land planning and management by providing efficient and reliable numerical modelling approaches. This will support the landslide risk evaluation, hazard mitigation and long-term land management, from which the environmental, social, and economic benefits can be achieved. As a result, the decision makers would have greater confidence in slope failure risk assessments on which they are basing their infrastructure investment considerations. Consequently, hazard warning systems, protections and land utilization regulations can be implemented, so that the loss of lives and properties can be minimized without investing in long-term, costly projects of ground stabilization.

在英国和全球范围内，各种规模的边坡失稳对弹性城市的可持续发展产生了至关重要的影响，因为它的发生会严重威胁人口，基础设施，公共服务和环境。例如，英国地质调查局估计，英国10%的斜坡被归类为中度至严重滑坡风险，超过7%的主要交通网络位于这些地区。这些斜坡可能会在长时间的潮湿天气或更密集的短期降雨事件中倒塌。目前，公众对边坡失稳风险的认识已经很高，但对其基本失稳机理和防治措施的认识还很有限。这主要是由于在分析多尺度响应和表征的材料属性的空间不均匀性的斜坡的困难。实验室和数值研究与成熟的经验模型可以解释一些特定的边坡失稳事件的一般特征，但不能普遍适用。一些具有挑战性的问题需要解决，如i）如何建立可靠的数学模型与多尺度模拟能力，以分析斜坡的渐进破坏？ii）如何处理真实的边坡的空间变异性和不确定性，例如材料性质、裂缝、流体渗透性？（iii）如何准确估计滑坡的扩展及其对基础设施的影响？这些挑战的基本科学问题是不同尺度下非均质边坡的弱化机制，因为它决定了不同地质和环境条件下的边坡响应。拟议的研究旨在通过多尺度和概率模拟方法探索渐进边坡破坏的基本机制及其对基础设施的影响。它使边坡的大变形问题可以方便地用有限元法作为边值问题进行分析，而土体的局部破裂、开裂或不连续行为可以通过离散元法在更小的离散子域中进行分析。离散元法的边界条件是由有限元网格的整体变形导出的。在分析中，土壤/岩石特性（例如弹性模量、摩擦系数、强度和流体渗透性）将作为具有空间变异性的随机场进行评估。数值模拟可以有效地弥合微观材料特性和整体宏观边坡响应之间的差距。在数值模拟中，可以有效地研究材料的不均匀性和不连续性对边坡破坏和随后的滑坡扩展的贡献。当加载应力超过微观尺度下颗粒结合强度时，内部断裂会自然发生，避免了传统连续介质模型中某些唯象本构定律的使用。作为一项多学科研究，本项目将涉及岩土工程、计算岩土工程、地质学、统计学、土/岩石力学和颗粒力学等学科。拟议的数值模型将有利于所有研究人员和利益相关者在土地规划和管理提供有效和可靠的数值模拟方法。这将支持滑坡风险评估、减灾和长期土地管理，从而实现环境、社会和经济效益。因此，决策者将对斜坡崩塌风险评估有更大的信心，他们是根据基础设施投资考虑的。因此，可以实施灾害预警系统、保护和土地利用条例，从而可以尽量减少生命和财产损失，而无需投资于长期、昂贵的地面稳定项目。

项目成果

Study on the non-linear deformation and failure characteristics of EPS concrete based on CT-scanned structure modelling and cloud computing

基于CT扫描结构建模和云计算的EPS混凝土非线性变形破坏特性研究

• DOI: 10.1016/j.engfracmech.2021.108214
• 发表时间: 2022
• 期刊: Engineering Fracture Mechanics
• 影响因子: 5.4
• 作者: Feng X

Failure mechanism of boulder-embedded slope under excavation disturbance and rainfall

• DOI: 10.1007/s10064-023-03369-z
• 发表时间: 2023-08
• 期刊: Bulletin of Engineering Geology and the Environment
• 影响因子: 4.2
• 作者: Xiang Yu;Tao Zhao;Bin Gong;Chun’an Tang

Modeling the single particle crushing behavior by random discrete element method

• DOI: 10.1016/j.conbuildmat.2023.134519
• 发表时间: 2024-01
• 期刊: Construction and Building Materials
• 影响因子: 7.4
• 作者: Du-min Kuang;Zhi-lin Long;Tao Zhao;Biao Luo;I. Ogwu;Feng-lan Kuang

Analysis of slope fracturing under transient earthquake loading by random discrete element method

• DOI: 10.1016/j.ijrmms.2022.105171
• 发表时间: 2022-09
• 期刊: International Journal of Rock Mechanics and Mining Sciences
• 影响因子: 7.2
• 作者: Tao Zhao;G. Crosta;Yong Liu

Investigating projectile penetration into immersed granular beds via CFD-DEM coupling

• DOI: 10.1007/s10035-023-01364-5
• 发表时间: 2023-09
• 期刊: Granular Matter
• 影响因子: 2.4
• 作者: Jiayu Lin;Tao Zhao;Mingjing Jiang