• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.445-454
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• 2008

Many countermeasures for local scour at bridge piers constructed on the river and sea have been developed and researched to protect piers against local scour. The most commonly employed method is riprap protection, which is sometimes required the filter installation between riprap and base layers. However, the construction of stone filters are really hard to perform in the field, require the high cost, or sometimes are impossible. The experimental modeling is conducted to analyze the riprap failure modes and the stability of riprap protection without filters based on the different approach velocity and riprap layer thickness conditions. Also, the stability index to evaluate the performance of riprap protection is developed using the experimental results. The cover and thickness of the riprap layer play a very important role in the stability and thicker riprap layers can prevent a total disintegration of the riprap layer effectively, especially due to winnowing failure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.63-71
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• 2009

Riprap filter should be installed around the pier to prevent riprap subsidence due to sediment winnowing or leaching between the riprap and bed layers. However, riprap protection without filters is commonly applied in the field because of ambiguous specifications and technical and economical difficulties to install the filter layer. Therefore, the hydraulic experiments were conducted in this study to measure and analyze the riprap subsidence quantitatively with different conditions for thickness of riprap layer, approached velocity, sizes of riprap and bed material. As the velocity was increased and size of bed material and thickness of riprap layer were decreased, the subsidence was increased. Consequently, the dimensionless riprap subsidence equation was derived using the synthesized experimental results. The results of this study could be employed as a standard criterion or predictor to evaluate the subsidence stability.