RETRACTED ARTICLE: Adaptive neuro-fuzzy estimation of the influence of slot on local scour at bridge pier groups

Abstract

Scouring around bridge pier is a major cause of bridge instability. Thus, providing appropriate methods in order to reduce and control the scour depth have received much attention. Using a slot in the bridge piers is one of modern methods of reducing bridge local scouring. In the present study, the effects of a rectangular slot on local scour mitigation around bridge pier groups have been investigated with adaptive neuro-fuzzy (ANFIS) method. ANFIS shows very good learning and prediction capabilities, which makes it an efficient tool to deal with encountered uncertainties in any system like scouring. The results show that the scour depth increased in the first pier by reinforcing effect and it decreased in the rear piers because of sheltering effect in compare with single pier. In addition, application of the slot in pier groups leads to an increase in the impact of reinforcing effect and reduce the influence of sheltering effect. The use of slot is more influential in front bridge piers than the rear piers in pier groups with 4D distance, however, this effectiveness doesn’t have significant difference among the piers with 2D distance and same as single pier. Laboratory experiments were conducted to create experimental training and checking data for ANFIS network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.