random field simulation
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Author(s):  
Chao Shi ◽  
Yu Wang

Consolidation analysis is a key task for reclamation design. Although consolidation is a long-term process, acceleration of consolidation is often preferred for speeding up the reclamations. Before proposing measures to accelerate consolidation and reclamation process, it is imperative to have an accurate prediction of consolidation settlement for fine-grained materials, which is greatly affected by spatial distribution of subsurface zones with different soil types (i.e., stratigraphic heterogeneities and uncertainty) and spatial variability of soil properties. In current practice, calculation of consolidation settlement often uses simplified stratigraphic boundaries and deterministic consolidation parameters without considering stratigraphic uncertainty or soil property spatial variability. The oversimplified practice might result in unconservative estimations of consolidation settlement and pose threats to safety and serviceability of constructed facilities on reclaimed lands. In this study, a stochastic framework is proposed for consolidation settlement assessment with explicit modeling of stratigraphic uncertainty and spatial variability of soil properties by machine learning and random field simulation from limited site investigation data. The proposed method effectively generates multiple realizations of geological cross-section and random field samples of geotechnical properties from limited measurements and offers valuable insights into spatial distribution of the estimated total primary consolidation settlement curves and angular distortion.


2019 ◽  
Vol 345 ◽  
pp. 283-301 ◽  
Author(s):  
Carl Scarth ◽  
Sondipon Adhikari ◽  
Pedro Higino Cabral ◽  
Gustavo H.C. Silva ◽  
Alex Pereira do Prado

2012 ◽  
Vol 138 (6) ◽  
pp. 711-715 ◽  
Author(s):  
Yufeng Gao ◽  
Yongxin Wu ◽  
Yuanqiang Cai ◽  
Hanlong Liu ◽  
Dayong Li ◽  
...  

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