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Design and analysis of geosynthetic-reinforced and floating column-supported embankments

岩土工程 堤防 土工合成材料 承载力 基础(证据) 栏(排版) 土壤水分 工程类 结构工程 地质学 连接(主束) 历史 土壤科学 考古
作者
Tuan A. Pham
出处
期刊:International Journal of Geotechnical Engineering [Informa]
卷期号:16 (10): 1276-1292 被引量:18
标识
DOI:10.1080/19386362.2021.1997209
摘要

Geosynthetic-reinforced column-supported system is an economic and effective solution to support embankments constructed on soft soils. In this solution, both end-bearing and floating columns are commonly used in practice. For deep soil foundation depths, floating columns are more economical than end-bearing piles. The design of a floating column foundation involves complex soil–structure interactions and there are still no clear uniform guidelines available for the design of embankments supported by floating columns. The main focus of this paper is to present a design method for the geosynthetic-reinforced floating column-supported (GRFCs) embankments. The main features of the proposed method are combining the bearing capacity theory for the floating columns, the arching theory for fill soils, the tensioned membrane theory for the geosynthetic, and considering interaction models between geosynthetic, soil, and piles. Using the proposed method, the influences of the pile geometry, soft clay, geosynthetic, and embankment fills properties were investigated. It was observed that the geosynthetic membrane inclusion enhances the load transfer mechanism and reduces significantly the differential settlements of floating pile-supported embankments. The floating columns with a higher ultimate bearing capacity cause more soil arching. In general, the soil shear strength properties and column geometry (length, diameter, column spacing) have a strong influence on the GRFCs embankment behaviour. Finally, the proposed method is compared with the BS 8006–1 and EBGEO design standards considering several experimental and numerical models to investigate its validity. The results showed that the proposed method is able of very good prediction performance and allows conducting the design optimization of GRFCs embankment.

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