Development of a local scour prediction model clustered by soil class

Abstract

Several studies have been conducted to assess local scour formulas in order to select the most appropriate one. Confronted to the limits of the previous formulas, further studies have been performed to propose new local scour formulas. Generalizing a single scour formula, for all soil classes, seems approximate for such a complex phenomenon depending on several parameters and may eventually lead to considerable uncertainties in scour estimation. This study aims to propose several new scour formulas for different granulometric classes of the streambed by exploiting a large field database. The new scour formulas are based on multiple non-linear regression (MNLR) models. Supervised learning is used as an optimization tool to solve the hyper-parameters of each new equation by using the ‘Gradient Descent Algorithm’. The results show that the new formulas proposed in this study perform better than some other empirical formulas chosen for comparison. The results are presented as seven new formulas, as well as abacuses for the calculation of local scour by soil classes.

Analytic network process for local scour formula ranking with parametric sensitivity analysis and soil class clustering

“…Several formulas exist for estimating scouring. Generally, these formulas neglect the soil class variation (Annad et al 2021).…”

“…Some formulas may contain in their equations some characteristics related to the streambed, such as the grain size 'D 50 ', the critical velocity 'V c ', etc. Nevertheless, including 'D 50 ' in the scour estimation seems inaccurate, for the simple reason that D 50 has low values compared to the other parameters, and considering it in the calculation instead of its characteristics can skew the outcome result (Annad et al 2021). Different erosion behaviors were identified by (Briaud et al 2001) for a variety of soil types with similar particle sizes.…”

“…Table 3 can be used as a first step to describe the performance of each formula through its statistical results as mentioned above (Annad et al 2021). The first step in comparing and validating the formulas used in this study is to compare the scour depths calculated by the formulas with the scour depths recorded in the field by submitting each of them to statistical performance criteria as stated in Table 3.…”

Analytic Network Process for Local Scour Formulas Ranking with Parametric Sensitivity Analysis and Soil Class Clustering

“…Some formulas include the characteristics related to the streambed, such as a grain size 'D50', Critical velocity 'Vc', etc.). Nevertheless, including 'D50' in the scour estimation seems inaccurate, for the simple reason that D50 has small values compared to the other parameters, and considering it in the calculation instead of its characteristics can skew the outcome result (Annad et al, 2021). For several types of soil with the same size of particles, different behavior of erosion has been identified by (Briaud et al, 2001).…”

“…Table 3 can be used as a first step to describe the performance of each formula through its results provided for each of the three statistical criteria mentioned above (Annad et al, 2021). The first step in comparing and validating the formulas used in this study is to compare the scour depths calculated by the formulas with the scour depth recorded in the field, by submitting each of them to statistical performance criteria.…”