IAHR World Congress, 2019

Maximum Scour Depth Relationships and Its Performances Around Circular Bridge Piers

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Civil Engineering, Indian Institute of Technology Roorkee, India

Scour is a natural process, caused by the intervention in a natural system and defined as the removal of stream bed-particles due to the erosive action of flowing water. It is a major factor in pier failure. Accurate prediction of scour depth around the pier can lead to the economic design of piers and avoid scour hazards instances. Present research primarily deals with maximum scour depth in cohesionless sediment under clear water scour condition. Several relationships are existing for predicting maximum as well as temporal scour depth near a circular pier. The present research defines the phenomenon of maximum equilibrium scour depth around the circular pier and deals with different pier scour prediction methods. The accuracy of five maximum scour depth relationships i.e. HEC-18, Sheppard et al. (2004 and 2013), Khan et al. (2012) and Guo (2014) are also examined in this research by using clear water scour data available in the literature as well as present experimental data. The graphical and statistical analysis illustrates the relationship given by Sheppard et al. (2013) achieved the best results in laboratory experimental data, whereas, over predicts for field data. Experimentally, it is noted that the median particle size in terms of densimetric Froude number shows a major effect on maximum equilibrium scour depth. Other factors have been gotten only inferior importance on maximum scour. It was also noted that the maximum scour depth always occurs at the upstream face of the pier nose and eroded sediment particles are dumped at the downstream side. In the present reaserch, three equilibrium scour time relationships i.e. Summer et al. (1992), Melville and Chiew (1999) and Choi and Choi (2016) are also used for checking the accuracy of equilibrium time of scour. For the equilibrium time of scour, the relationship given by Choi and Choi (2016) gives good results with observed data.

MANISH PANDEY
MANISH PANDEY








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