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

河流浮冰的堆积和堵塞，被称为冰塞，是加拿大河流洪水的重要原因。因此，预测何时何地可能发生冰塞，对于估计潜在的洪水、评估相关风险和规划应对措施至关重要。然而，即使在计算技术和数值模型方面取得了最新进展，这种预测仍然超出了现有预测工具的能力。这是由于冰塞的复杂性质以及导致其发生和形成的条件，这取决于许多因素，包括冰的特性、水动力和热力学以及水道的形态。因此，拟议的项目旨在开发一个复杂的数值模型，能够预测冰阻塞的形成，并将其应用于研究导致冰阻塞发生的关键条件，适用于加拿大（特别是魁北克）的河流。提出的模型将基于三维高性能混合无网格拉格朗日技术，该技术以其处理高动态多物理场问题的能力而闻名，因此能够再现冰水相互作用和冰塞开始和形成的详细物理现象。模型结果与实验数据相结合，有望建立起冰塞起爆与关键有效参数（如冰的大小和浓度、河流形态和流动条件）临界值之间的关系。因此，提出的研究将提供一个新的认识，否则难以预测的果酱起爆。这将大大提高冰塞的可预测性，这在预防和减轻与冰塞和由此产生的洪水及其破坏性社会经济影响有关的风险方面具有关键作用，特别是在加拿大和魁北克的河流中。

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.