Home Bearing capacity of floating geosynthetic encased columns (GEC) determined on the basis of CPTU penetration tests
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Bearing capacity of floating geosynthetic encased columns (GEC) determined on the basis of CPTU penetration tests

  • Iwona Chmielewska EMAIL logo
Published/Copyright: July 14, 2020
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Abstract

Floating geosynthetic encased columns (GEC) are an increasingly popular method of strengthening weak subsoil. Design of floating columns is a difficult and not fully recognized issue. This paper treats the floating GEC column as a special kind of “pile” and its bearing capacity is calculated using five selected methods for calculating the bearing capacity of piles based on CPTU penetration tests. The calculations were done on the basis of insitu tests carried out on one of the sections of the Bargłów Kościelny bypass. The paper contains a comparison of the bearing capacities of floating GEC columns calculated with different methods based on CPTU penetration tests.

1 Introduction

A floating column is a column with a base in weak subsoil. Floating columns are an increasingly popular method of strengthening weak subsoil, mainly for economic and technological reasons [1]. Guidelines for the design of reinforcement for geosynthetic encased columns (GEC) [2] apply only to end-bearing columns, and there are no guidelines for designing reinforcement for floating columns.

The floating GEC column can be treated as a special kind of “pile” and its bearing capacity can be calculated with methods based on CPTU penetration tests [3].

2 Methods of calculating the bearing capacity of piles based on CPTU tests

In this paper, the bearing capacity of the column was determined by five selected methods: LCPC [4], Beringen and De Ruiter [5], DIN 4014 [6], Schmertmann [7] and Philipponnat [8].

Pile bearing capacity is the sum of the base capacity Qbk and shaft capacity Qsk [9]:

(1)Qk=Qbk+Qsk
(2)Qbk=qbAk
(3)Qsk=fpAs

where Ak and As are the area of the pile base and pile shaft respectively, qb is the unit end-bearing pressure and fp is the average shaft resistance.

2.1 LCPC method

In the Laboratoire Central des Ponts et Chausees (LCPC) method, the unit end-bearing pressure and average shaft resistance can be calculated directly from the tip cone resistance qc [4].

(4)qb=kcqc,avg
(5)fp=qc,zα

where kc, α are coefficients that depend on the pile and soil type, qc,avg is the equivalent average cone resistance between 1.5Dk below and 1.5Dk above the pile tip, Dk is the diameter of the pile and qc,z is the cone resistance at depth zk.

The value qc,avg should be calculated in three steps:

  • Calculate qac as a mean value of qc at a depth between 1.5Dk below and 1.5Dk above the pile tip.

  • Eliminate qc values higher than 1.3qac and lower than 0.7 qac.

  • Calculate qc,avg within the range defined in the previous step.

2.2 Beringen and De Ruiter method

In the Beringen and De Ruiter method, also known as the European method, the values of qb and fp in Equations 2 and 3 should be determined from the following equations [5]:

(6)qb=9cu
(7)fp=βcu

where β = 1 for normally consolidated soils, β = 0.5 for over consolidated soils and cu is the undrained shear strength determined from Equation 8 [10].

(8)cu=qtσv0Nkt

where qt is the corrected cone resistance, σv0 is the total initial stress at the considered depth, Nkt is a coefficient depending on the plasticity index Ip and the degree of soil consolidation. Nkt values are usually in the range of 10 to 20 [11].

2.3 DIN 4014 method

In the DIN 4014 method, the shaft resistance fp and the unit end-bearing pressure qb in cohesive soils are determined from the undrained shear strength cu.

The value of cu can be determined from Equation 8, using an average qc value over a zone of three times the pile diameter under the tip.

2.4 Schmertmann method

In the Schmertmann method, the value of qb is determined from Equation 9 [7].

(9)qb=qc1+qc22

where qc1 is the minimum average value of the cone resistance at a depth of 0.7Dk or 4Dk below the pile tip and qc2 is the minimum average value of the cone resistance in the zone equal to 8Dk above the pile tip.

For piles with a base in cohesive soils, the fp value can be determined from Equation 10 [7].

(10)fp=αcfs

where fs is the sleeve friction and αc is a coefficient selected in the range 0.2 to 1.25, depending on the sleeve friction and the type of pile. For values of fs equal to 30 kPa and less, the value of the coefficient αc is the same for all types of piles.

2.5 Philipponnat method

In the Philipponnat method, the values of qb and fp can be determined from Equations 11 and 12 [8].

(11)qb=kbqca=kbqca(A)+qcb(B)2
(12)fp=αsFsqcs

where kb is a coefficient that depends on the type of soil in which the pile tip is located (for clays, kb = 0.5), qca(A) is the average cone resistance in the zone equal to 3B above the pile tip, qcb(B) is the average cone resistance at a depth of 3B below the pile tip, Fs is a coefficient depending on the type of soil in which the pile tip is located (for clays, Fs = 50), αs is a coefficient equal to 1.25 and qcs is the average cone resistance along the pile shaft. For circular foundations B = B and a B value can be calculated from Equation 13.

(13)B=12πDk0.886Dk

3 Calculation arrangements

The GEC column is treated as a special kind of “pile” and its bearing capacity is calculated using five selected methods for determining the pile bearing capacity based on CPTU tests.

This paper considers the characteristic value of the bearing capacity Qk (Figure 1) of a single column for reinforcingweak subsoil for plans with large dimensions (road embankments, spatial structures). Negative friction was omitted in the calculations because the reinforced soil mattress on the subsoil causes settlement of the column and the weak subsoil surrounding the column to be equal. The calculations were carried out for columns with diameter Dk equal to 0.8 m.

Figure 1 Geometry of the problem.
Figure 1

Geometry of the problem.

The bearing capacity of floating GEC columns was determined on the basis of CPTU tests carried out on one of the sections of the Bargłów Kościelny bypass, where a weak subsoil was reinforced with floating GEC columns.

On the analyzed section of the Bargłów Kościelny bypass, there are organic soils, mainly peat with a thickness of from about 3 m to about 9 m. Below the organic soils there are glacial deposits in the form of sandy clays. On top of the layer of glacial deposits, the clays are soft. With depth, the moisture of the cohesive soils decreases, and thus the liquidity index decreases, dropping to a value corresponding to stiff clay. The ground water level is located at a depth of 0.2–0.3 m below the ground surface.

The relationships between the liquidity index IL of sandy clay and the cone resistance qc, undrained shear strength cu and sleeve friction fs were determined on the basis of the CPTU penetration tests (Figure 2).

Figure 2 Relationships between: a) qc – IL, b) cu – IL, c) fs – IL.
Figure 2

Relationships between: a) qcIL, b) cuIL, c) fsIL.

Bearing capacity of the columns was calculated for soil conditions determined in four selected locations located on the section of Bargłów Kościelny bypass under consideration. The analyzed locations were spaced about 30mapart. The calculations weremade for different depths of columns in the weak subsoil zk (Figure 1) equal to 0, 0.75, 1.5 and 3.0 m for location 1 and 4; 0, 0.75, 1.5 and 2.5 for location 2; and 0, 0.75, 1.5 and 2.0 for location 3.

Different values of the maximum depth for locations 2 and 3 are due to the fact that a depth of 3 m would mean that the tip of the column would be located in stiff soil and the column would not be a floating column.

Figure 3 presents the results of the CPTU tests in the four selected locations located on the section of the Bargłów Kościelny bypass under consideration and the thickness of the layers of peat and sandy clay with a variable liquidity index IL.

CPTU tests were carried out to a depth of about 12 m, which wouldbe insufficient to make calculations based on the cone resistance graphs; therefore a forecast of the liquidity index was made to a depth of 20 m (Figure 3).

Figure 3 Results of CPTU tests: a) location 1, b) location 2, c) location 3, d) location 4.
Figure 3

Results of CPTU tests: a) location 1, b) location 2, c) location 3, d) location 4.

Table 1 shows the values of the cone resistance, sleeve friction and undrained shear strength from Figure 2 for different liquidity indexes of the sandy clay located at the tip of the floating GEC column.

Table 1

Parameters of the sandy clay determined on the basis of the CPTU penetration tests.

Degree of plasticity ILCone resistance qcSleeve friction fsUndrained shear strength cu
[-][kPa][kPa][kPa]
0.58676.111.0530.10
0.421193.423.6756.98
0.311679.934.6781.90

4 Bearing capacity of the floating GEC columns

Figure 4 shows the bearing capacity of the floating columns at different depths of the column tip in the soft sandy clay for the five selected calculation methods.

Figure 4 Bearing capacity of the floating GEC columns: a) location 1, b) location 2, c) location 3, d) location 4.
Figure 4

Bearing capacity of the floating GEC columns: a) location 1, b) location 2, c) location 3, d) location 4.

5 Conclusions

From the calculations, comparable values of the column bearing capacity were obtained for the five calculation methods analyzed in this paper. Differences in the values for the different calculation methods are due to the different assumptions on which the methods were based.

In all the analyzed locations, the lowest bearing capacity of the column was determined using the LCPC method. The highest bearing capacity was calculated using the European and Schmertmann methods, and for location 3, using the DIN 4014 method.

The bearing capacity of the columns increased with increasing depth of the column tip in sandy clay. A more than three times higher bearing capacity that varied with the depth was observed in location 1.

The highest bearing capacity was determined for the columns in location 3, while the smallest was for the columns in location 1. This can be related to the soil conditions in each individual location.

The methods of determining the bearing capacity of floating GEC columns described in this paper do not allow the distribution of the load in the columns and weak subsoil to be included in the calculations; thus, it does not take into account cooperation between the column and the surrounding soil. However, the author believes that these methods can be successfully used to pre-estimate the bearing capacity of floating GEC columns based on the results of CPTU penetration tests.

Main Nomenclature

Ak

column base area

As

column shaft area

cu

undrained shear strength

Dk

column diameter

fp

shaft resistance

fs

sleeve friction

IL

liquidity index

Qbk

column base capacity

qb

unit end-bearing pressure

qc

cone resistance

Qk

column bearing capacity

Qsk

column shaft capacity

qt

corrected cone resistance

zk

depth of the column base

CPTU

cone penetration test

GEC

geosynthetic encased column

Acknowledgement

This paper, carried out at Bialystok University of Technology, was supported by Polish financial resources on science under project WZ/WBiIŚ/7/2019.

References

[1] Ng KS, Tan SA. Design and analyses of floating stone columns. Soils and Foundations. 2014;54(3):478-87.10.1016/j.sandf.2014.04.013Search in Google Scholar

[2] EBGEO. Recommendations for Design and Analysis of Earth Structures using Geosynthetic Reinforcements. Berlin, Germany: Ernst & Sohn. A Wiley Company; 2011.Search in Google Scholar

[3] Chmielewska I. Wpływ technologii wykonania zawieszonej kolumny GEC na jej nośność i osiadanie [dissertation]. Bialystok University of Technology; 2019. Polish.Search in Google Scholar

[4] Bustamante M, Gianeselli L. Pile bearing capacity prediction by means of static penetrometer CPT. Proceedings of the Second European Symposium on Penetration Testing; 1982 May 24-27; Amsterdam, The Netherlands. USA: MBS; 1982. p. 493-500.Search in Google Scholar

[5] De Ruiter J, Beringen FL. Pile foundation for large North Sea structures. Marine Geotechnology. 1979;3(3):267-314.10.1080/10641197909379805Search in Google Scholar

[6] DIN 4014: 1990-03. Bored cast in place piles – Formation, design and bearing capacity; 1990.Search in Google Scholar

[7] Schmertmann JH. Guidelines for cone penetration test, performance and design. Final Report. United States Department of Transportation (Washington); 1978 Dec. Report No. FHWA-TS-78-209.Search in Google Scholar

[8] Philipponnat G. Methode pratique de calcul d’un pieu isole a l’aide du penetrometre statique. Revue Francaise de Geotechnicue. 1980;10:55-64. French.10.1051/geotech/1980010055Search in Google Scholar

[9] Schnaid F. In situ testing in geomechanics. The main tests. London and New York: Taylor & Francis; 2009.10.1201/9781482266054Search in Google Scholar

[10] PN-EN 1997-2. Eurokod 7: Projektowanie geotechniczne – Część 2: Rozpoznanie i badanie podłoża gruntowego; 2009. Polish.Search in Google Scholar

[11] Kowalska M, Orzeł A. Identyfikacja rodzaju gruntu oraz parametrów wytrzymałościowych podłoża na podstawie wyników badań sondą statyczną CPTU. Przegląd Komunikacyjny. 2014;8:31-6. Polish.Search in Google Scholar

Received: 2019-07-25
Accepted: 2020-05-13
Published Online: 2020-07-14

© 2020 I. Chmielewska, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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