Fully-Lagrangian three-dimensional modelling of river ice jam initiation

河流冰塞引发的全拉格朗日三维建模

• 批准号: 558609-2020
• 负责人: Shakibaeinia, Ahmad
• 金额: $ 1.46万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=706823
• 关键词: Fully; Lagrangian; three; dimensional; modelling

Accumulation and blockage of floating river ice parcels, called ice jam, is a significant cause of flooding in Canadian rivers. Therefore, prediction of where and when the ice jam may happen is essential for estimation of the potential flooding, assessment of the associated risk, and planning responses. Nevertheless, even with the latest advancement in computational techniques and numerical models, such prediction is still beyond the capabilities of existing predictive tools. This is due to the complex nature of ice jams and the conditions leading to its initiation and formation, which depend on a large number of factors including the ice characteristics, and the hydrodynamic and thermodynamic and morphology of the watercourse. The proposed project, therefore, aims at developing a sophisticated numerical model, capable of predicting the ice jam formation and applying it for investigating the critical conditions leading to jam initiation over ranges applicable to Canadian (esp., Quebec) rivers. The proposed model will be based on a three-dimensional high-performance hybrid mesh-free Lagrangian technique, which is known for its ability to deal with highly dynamic multi-physics problems, and hence is capable of reproducing the detailed physics of ice-water interactions and ice jam initiation and formation. The model outcomes, in combination with the experimental data, are expected to establish the relationship between the ice jam initiation and the critical value of the key effective parameters such as ice size and concentration, river morphology, and flow conditions. Therefore, the proposed research will provide a new understanding of the otherwise difficult to predict jam initiation. This will significantly improve the ice jams predictability, which has a crucial role in the prevention and mitigation of the risks associated with the jams and resulting floods and their devastating socio-economic impacts, particularly in Canadian and Quebec rivers.

浮动河冰块的积累和阻塞称为冰果酱，是加拿大河流洪水的重要原因。因此，预测可能发生冰果上以及何时发生的冰淇淋对于估计潜在的洪水，评估相关风险和计划反应至关重要。然而，即使在计算技术和数值模型方面取得了最新的进步，这种预测仍然超出了现有预测工具的功能。这是由于冰果酱的复杂性质以及导致其启动和形成的条件，这取决于许多因素，包括冰的特征以及水道的流体动力和热力学和形态。因此，拟议的项目旨在开发一个复杂的数值模型，能够预测冰果酱的形成，并将其应用于调查关键条件，从而导致适用于加拿大河流（Queebec）河流的范围内果酱的启动。提出的模型将基于三维高性能混合无网状拉格朗日技术，该技术以处理高度动态的多物理问题的能力而闻名，因此能够再现冰水的详细物理学相互作用和冰果冻的启动和形成。该模型的结果与实验数据结合在一起，有望建立冰果酱启动与关键有效参数的临界值（例如冰和浓度，河流形态和流动条件）之间的关系。因此，拟议的研究将对原本难以预测果酱开始的新理解。这将显着改善冰果酱可预测性，这在预防和减轻与果酱相关的风险以及造成的洪水及其毁灭性的社会经济影响方面具有至关重要的作用，尤其是在加拿大和魁北克河流中。