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.
翻译:实时传感器监测被证明是减少与这些不断演变的填土结构有关的风险的关键工具,这些结构的突然和危险失灵率很高。为了最佳利用实时堤岸监测,必须克服一个主要障碍:建立稳定分析支持数字模型,对实时进行数据同化作出迅速反应;应建立一个模型,使其反应速度快于所分析现象的物理演变。在这项工作中,采用减序建模(ROM)来提高计算效率,解决管理这一问题的混合水文-机械方程式系统。减式方法适用于管理地下水流动的混合水力-机械方程式,由于考虑不饱和土壤而使这些方程式变得非线性。由此形成的模型的性能通过解决与尾部水力-建模有关的2D问题和3D问题加以评估。降低定型模型用于解决水力-机械化等式组合的计算效率,同时保持3M-M-M-M的高度安全度。