Research Output

Influence of gravel density in the behaviour of soft soils improved with stone columns

  Stone columns are frequently employed to improve the bearing capacity of soft soils, to reduce settlements, and to increase the speed of consolidation. Their behaviour depends on several factors, such as the density of the aggregate that forms the column and the area replacement ratio. This paper presents a study of the influence of the density of the gravel forming the columns on the deformation and stresses around end-bearing stone columns installed in soft soils. For this purpose, the behaviour of a horizontal slice of a unit cell has been analyzed by small-scale laboratory tests performed in a Rowe–Barden cell. Tests have been performed with a gravel relative density of Dr = 30% and with two area replacement ratios. Their results have been analyzed along with those from similar tests performed with a gravel density of Dr = 100%. The study is focused on the soil–column stress concentration ratio and the reduction of settlements. Finally, the experimental results are compared with numerical simulations. The results show that a reduction of settlements around 10% occurs when the relative density of the gravel increases from Dr = 30% to 100%. Numerical analyses reproduce well the behaviour of stone columns and are in good agreement with the experimental results.

  • Type:


  • Date:

    15 May 2015

  • Publication Status:


  • Publisher

    Canadian Science Publishing

  • DOI:


  • Cross Ref:


  • Library of Congress:

    TA Engineering (General). Civil engineering (General)

  • Dewey Decimal Classification:

    624 Civil engineering


Miranda, M., Da Costa, A., Castro, J. & Sagaseta, C. (2015). Influence of gravel density in the behaviour of soft soils improved with stone columns. Canadian geotechnical journal. Revue canadienne de géotechnique. 52(12), 1968-1980. doi:10.1139/cgj-2014-0487. ISSN 1208-6010



small-scale test, stone column, gravel density, settlement reduction, stress concentration factor, numerical analysis

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