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DInSAR data assimilation for settlement prediction: case study of a railway embankment in the Netherlands

机译:沉降预测的Dinsar数据同化:荷兰铁路堤防案例研究

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Secondary settlements in soft soils represent a significant fraction of the total settlement induced by external loads. Consequently, these settlements can play a key role in performance, serviceability, and safety of engineering works such as buildings, roads, embankments, and pipelines. This paper addresses the development of a predictive settlement model for a railway embankment built on soft clayey-peaty soils by following an original procedure consisting of three cascading steps: (i) preliminary detection of the most settlement-affected portions of the infrastructure; (ii) development of an equivalent subsoil model to study secondary settlements; (iii) back-calculation of the parameters of a predictive settlement model (design subsoil model) via a variational data assimilation scheme that exploits ground displacement measurements derived from differential interferometric synthetic aperture radar (DInSAR) data. The main achievement relies on the retrieval of a stochastic prediction of secondary settlements that can contribute to rationalize both conventional monitoring campaigns and management of key infrastructure.
机译:软土中的次级沉降是由外部载荷引起的总沉降的显着分数。因此,这些定居点可以在工程,可维护性和工程工作的安全性中发挥关键作用,例如建筑物,道路,堤防和管道。本文通过遵循由三个级联步骤组成的原始程序,解决了在软粘土 - 泥质土壤中建立的铁路路堤预测解决模型的开发:(i)初步检测基础设施最具解决受影响的部分; (ii)发展次级定居点等同的底土模型; (iii)通过变分数据同化方案来回计算预测结算模型(设计Subsoil模型)的参数,该变分数据同化方案利用差分干涉性合成孔径雷达(Dinsar)数据的接地位移测量。主要成就依赖于检索对二次定居点的随机预测,这有助于合理化传统监测活动和关键基础设施的管理。

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