Assessment of the spatial variability of a Croatian flood embankment using the cone penetration test

Reale, C.; Kovačević, Meho Saša; Bačić, Mario; Gavin, K.G.

doi:10.1201/9781003308829-159

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“…In any other case, the percentages would be misleading; instead, new analyses should be conducted following the same methodology. Further improvements can be made by defining the corresponding levee parameters as random variables with known distributions [18][19][20][21][22] and then conducting a variation of the SB method by Cheng [5], which allows for the output to be stochastic. This would surely affect the classification of the important parameters as their variations are taken into consideration, contrary to the analyses in this paper, where the inherent soil variation is considered negligible.…”

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confidence: 99%

Methodology for Identification of the Key Levee Parameters for Limit-State Analyses Based on Sequential Bifurcation

et al. 2023

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Levees are linear structures that are continuously reconstructed throughout the years and whose construction and behavior depends on local soil conditions, as well as requirements regarding impermeability and mechanical resistance. This results in various levee cross sections, even within the same levee. In situations of extreme water events, when timely actions are required, this variability poses a problem for decision-making based on observed behavior, which is highly dependent on the specific section parameters. Creating models for each problematic section becomes impractical, and because of that, in this study, 91 different cross sections from 16 levees are considered to identify the key levee parameters with the largest effects on three observed mechanisms: deformations, exit hydraulic gradients, and factors of safety. The implemented factor screening methodology is based on the sequential bifurcation method (SB) and numerical analyses. The SB method successively investigates groups of factors and uses their cumulative effects to identify the important groups and to discard the unimportant based on a previously selected parameter Δ, until the groups are reduced to single factors that may be deemed important. It is found that approximately 30% of all the factors used to describe the most complex sections are considered important by at least one of the investigated mechanisms.

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