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== Abstract ==
 
== Abstract ==
  
The suffusion susceptibility of the soil samples is evaluated through an erosion resistance index. 13 Thanks to existing statistical analyses, the erosion resistance index is estimated from several soil parameters. In 14 actual exploitation, the soil properties with the input parameters related to the grain distribution of the soil… 15 vary greatly from the original design value due to the influence of many factors. One of the factors is the 16 inherent variability. Inherent soil variability is modelled as a random field. The usual problems used to assess the 17 suffusion susceptibility may be not give accurate results or fully evaluate the actual working ability of the ground 18 in each case. This is one of the reasons why dams are still eroded when they are put into use. The paper aims 19 predict erosion resistance index of the earth dam using two-dimensional (2D) Stochastics random field, 20 modelling the initial problem, considering the variability spatial of soil properties, using the assumption of a 21 Normal random field of soil characteristics parameters. The paper shows the predicted results of the variability 22 spatial of erosion resistance index of Phu Vinh dam-Vietnam. Furthermore, the paper also represents the 23 happened probability of suffusion susceptibility at the different zones in the earth dam body. 24
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The suffusion susceptibility of the soil samples is evaluated through an erosion resistance index. Thanks to existing statistical analyses, the erosion resistance index is estimated from several soil parameters. In actual exploitation, the soil properties with the input parameters related to the grain distribution of the soil… vary greatly from the original design value due to the influence of many factors. One of the factors is the inherent variability. Inherent soil variability is modelled as a random field. The usual problems used to assess the suffusion susceptibility may be not give accurate results or fully evaluate the actual working ability of the ground in each case. This is one of the reasons why dams are still eroded when they are put into use. The paper aims predict erosion resistance index of the earth dam using two-dimensional (2D) Stochastics random field, modelling the initial problem, considering the variability spatial of soil properties, using the assumption of a Normal random field of soil characteristics parameters. The paper shows the predicted results of the variability spatial of erosion resistance index of Phu Vinh dam-Vietnam. Furthermore, the paper also represents the happened probability of suffusion susceptibility at the different zones in the earth dam body.
  
 
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Revision as of 11:14, 15 March 2023

Abstract

The suffusion susceptibility of the soil samples is evaluated through an erosion resistance index. Thanks to existing statistical analyses, the erosion resistance index is estimated from several soil parameters. In actual exploitation, the soil properties with the input parameters related to the grain distribution of the soil… vary greatly from the original design value due to the influence of many factors. One of the factors is the inherent variability. Inherent soil variability is modelled as a random field. The usual problems used to assess the suffusion susceptibility may be not give accurate results or fully evaluate the actual working ability of the ground in each case. This is one of the reasons why dams are still eroded when they are put into use. The paper aims predict erosion resistance index of the earth dam using two-dimensional (2D) Stochastics random field, modelling the initial problem, considering the variability spatial of soil properties, using the assumption of a Normal random field of soil characteristics parameters. The paper shows the predicted results of the variability spatial of erosion resistance index of Phu Vinh dam-Vietnam. Furthermore, the paper also represents the happened probability of suffusion susceptibility at the different zones in the earth dam body.

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Published on 30/06/23
Accepted on 23/06/23
Submitted on 17/03/23

Volume 39, Issue 2, 2023
DOI: 10.23967/j.rimni.2023.06.007
Licence: CC BY-NC-SA license

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