|Title:||Numerical simulation of backward erosion piping in heterogeneous fields||Authors:||Liang Y.; Yeh T.-C.J.; Wang Y.-L.; Liu M.; Wang J.; Hao Y.
|Keywords:||Decision making; Erosion; Failure (mechanical); Groundwater flow; Intelligent systems; Risk assessment; Seepage; Stochastic systems; Backward erosion piping; Heterogeneity; Numerical algorithms; Preferential flows; Random fields; Spatial correlation structures; Spatial correlations; Stochastic parameters; Monte Carlo methods; algorithm; correlation; decision making; failure analysis; flow field; heterogeneity; hydraulic conductivity; levee; Monte Carlo analysis; numerical model; piping; preferential flow; probability; risk assessment; seepage; soil property; void ratio||Issue Date:||2017||Publisher:||Blackwell Publishing Ltd||Journal Volume:||53||Journal Issue:||4||Start page/Pages:||3246-3261||Source:||Water Resources Research||Abstract:||
Backward erosion piping (BEP) is one of the major causes of seepage failures in levees. Seepage fields dictate the BEP behaviors and are influenced by the heterogeneity of soil properties. To investigate the effects of the heterogeneity on the seepage failures, we develop a numerical algorithm and conduct simulations to study BEP progressions in geologic media with spatially stochastic parameters. Specifically, the void ratio e, the hydraulic conductivity k, and the ratio of the particle contents r of the media are represented as the stochastic variables. They are characterized by means and variances, the spatial correlation structures, and the cross correlation between variables. Results of the simulations reveal that the heterogeneity accelerates the development of preferential flow paths, which profoundly increase the likelihood of seepage failures. To account for unknown heterogeneity, we define the probability of the seepage instability (PI) to evaluate the failure potential of a given site. Using Monte-Carlo simulation (MCS), we demonstrate that the PI value is significantly influenced by the mean and the variance of ln k and its spatial correlation scales. But the other parameters, such as means and variances of e and r, and their cross correlation, have minor impacts. Based on PI analyses, we introduce a risk rating system to classify the field into different regions according to risk levels. This rating system is useful for seepage failures prevention and assists decision making when BEP occurs. © 2017. American Geophysical Union. All Rights Reserved.
|Appears in Collections:||生物環境系統工程學系|
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