Discussion of "Prediction of the undrained shear strength of remolded soil with non-linear regression, fuzzy logic, and artificial neural network" J. Mt. Sci. 21(9): 3108–3122
-
Graphical Abstract
-
Abstract
This opinion article discusses the original research work of Yünkül et al. (the Authors) published in the Journal of Mountain Science 21(9): 3108–3122. Employing non-linear regression, fuzzy logic and artificial neural network modeling techniques, the Authors interrogated a large database assembled from the existing research literature to assess the performance of twelve equation rules in predicting the undrained shear strength (su) mobilized for remolded fine-grained soils at different values of liquidity index (IL) and water content ratio. Based on their analyses, the Authors proposed a simple and reportedly reliable correlation (i.e., Eq. 9 in their paper) for predicting su over the IL range of 0.15 to 3.00. This article describes various shortcomings in the Authors' assembled database (including potentially anomalous data and covering an excessively wide IL range in relation to routine geotechnical and transportation engineering applications) and their proposed su = f(IL) correlation. Contrary to the Authors' assertions, their proposed correlation is not reliable for fine-grained soils with consistencies in the general firm to stiff range (i.e., for 0.15 < IL < 0.40), increasingly overestimating su for reducing IL, and eventually predicting su → +∞ for IL → 0.15+ (while producing mathematically undefined su for IL < 0.15), thus rendering their correlation unconservative and potentially leading to unsafe geotechnical designs. Exponential or regular-power type su = f(IL) models are more suitable when developing correlations that are applicable over the full plastic range (of 0 < IL < 1), thereby providing reasonably conservative su predictions for use in the preliminary design for routine geotechnical engineering applications.
-
-