The use of Internet of Things (IoT) technologies is becoming a preferred solution for the assessment of tailings dams' safety. Real-time sensor monitoring proves to be a key tool for reducing the risk related to these ever-evolving earth-fill structures, that exhibit a high rate of sudden and hazardous failures. In order to optimally exploit real-time embankment monitoring, one major hindrance has to be overcome: the creation of a supporting numerical model for stability analysis, with rapid-enough response to perform data assimilation in real time. A model should be built, such that its response can be obtained faster than the physical evolution of the analyzed phenomenon. In this work, Reduced Order Modelling (ROM) is used to boost computational efficiency in solving the coupled hydro-mechanical system of equations governing the problem. The Reduced Basis method is applied to the coupled hydro-mechanical equations that govern the groundwater flow, that are made non-linear as a result of considering an unsaturated soil. The resulting model's performance is assessed by solving a 2D and a 3D problem relevant to tailings dams' safety. The ROM technique achieves a speedup of 3 to 15 times with respect to the full-order model (FOM) while maintaining high levels of accuracy.

中文翻译：

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通过模型降阶实现对填土坝的实时评估

物联网 (IoT) 技术的使用正成为尾矿坝安全评估的首选解决方案。事实证明，实时传感器监控是降低与这些不断发展的填土结构相关的风险的关键工具，这些结构具有很高的突发性和危险性故障率。为了最佳地利用实时路堤监测，必须克服一个主要障碍：创建用于稳定性分析的支持数值模型，具有足够快的响应以实时执行数据同化。应该建立一个模型，以便可以比分析现象的物理演变更快地获得其响应。在这项工作中，降阶建模 (ROM) 用于提高求解控制问题的耦合流体力学方程组的计算效率。简化基法应用于控制地下水流动的耦合流体力学方程，由于考虑了非饱和土壤，这些方程变为非线性。通过解决与尾矿坝安全相关的 2D 和 3D 问题来评估所得模型的性能。相对于全阶模型 (FOM)，ROM 技术实现了 3 到 15 倍的加速，同时保持了高精度。