Pouyan Abbasi Maedeh^{1} , Wei Wu^{2} , Ali Ghanbari^{3} , Jia Lin^{4} , Marelianda Al Dianty^{5} , Kourosh Ghaffari Irdmoosa^{6} , Amir Shahraki Ghadimi^{7}
^{1, 2, 4}University of Bodenkultur, Vienna, Austria
^{3, 6, 7}Kharazmi University, Tehran, Iran
^{5}University of Brescia, Brescia, Italy
^{1}Corresponding author
Journal of Measurements in Engineering, Vol. 6, Issue 1, 2018, p. 1024.
https://doi.org/10.21595/jme.2018.19597
Received 2 January 2018; accepted 25 January 2018; published 31 March 2018
Copyright © 2018 JVE International Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The maximum displacement in a soil nail bond system considering the pullout, overburden load and grouting pressure effects has been evaluated. The Pullout tests were carried out in five sites that located in Tehran, Iran. Moreover, additional pullout test data from South Korea is considered. The displacement of the nailing system due to gravity and pressure grouting has been measured. Based on achieved data, four practical relationships between bound strength and pullout displacements are developed. The parameters overburden load, grouting pressure, borehole diameter, moisture content and soil’s strength parameters have been chosen as the major inputs for the relationships. The correlation coefficients of the linear relationship range have been achieved between 0.89 and 0.99. While by using the multilayer neural network for estimating it has been illustrated approximately 0.95.
Keywords: soil nail bond, pullout, relationship, grouting pressure.
The soil nailing system is one of the common methods to stabilize soil wall for deep excavated areas and surface of slopes [1, 2]. Low costing, no dependency on a lot of apparatus and effortless running are the significant advantages of the nailing system [3]. However, in some special cases of soil conditions, site geometry or loading, the nailing system may not be affordable or efficient [1]. The nailing system clearly has an increased activity in the soil shear strength [4].
A common nailing system has the steel bars with diameters between 2540 mm are prevalent to use as reinforcing elements [5, 6]. Rotary drilling, driven casing, augured and jet grouting are most widespread for coring between 95 to 120 mm diameters [1, 2]. Moreover, the length of drilled borehole directly related to bar length and slope or excavation height [1, 2]. The set of the borehole and its steel bar should be full of cement grouting or soft concrete [4, 7].
Most of the nails have been placed by using gravity pressure grouting. Occasionally, to increase bound strength the pressuregrouting technique has been done for nailing installation that grouting pressure most of the times would be considered between 3001000 kPa. While this technic has been demanded additional equipment such as pump, packer system and instrument tools. Furthermore, higher quality control compares with regular gravity pressure soil nails is necessary in case of pressure grouting. In addition, using pressure grouting system would be able to improve the grouting formation in the borehole [7], expand the diameter of the borehole and reducing the total number of used nails.
There is no a direct relationship to approximate the bound strength due to effective parameters and nailing system displacement and just in site experimental work such as pullout would be used. A substantial method to estimate the bound strength is presented in FHWA [1, 2]. The numerous of last studies have assessed the pullout conduct of gravity and pressure grouting nailing by using numerical simulation and laboratory or field tests [4, 6]. Some of the previous research on bound strength and nailing system displacement are [811].
The current work has been focused on to develop new practical relationships to estimate the outcome displacement for nailing system which may be resulted during pullout test considering soil conditions and site loading. Both cases of pressured and gravity grouting conditions would be considered. The base of input results has been generated by using the insite pullouts test and previous literature. Furthermore, linear regression is used to developing the relationships, while the multilayer neural network has been used for verification.
Twenty different pullout test has been conducted in five different place in Tehran, Iran. The places Tejrish, Artesh and Sayyad shirazi Highway areas are placed in the north and northeast of Tehran. While Sadeghiye and Shahrak gharb areas are located in west and northwest of Tehran respectively. Additional pullout the data have been taken from [11]. Information for the data type for each of sites has been presented in Table 1.
Table 1. The site name, location and the data types
Site No.

Name

Country

Type of data

1

Tajrish

Iran

Pullout

2

Artesh

Iran

Pullout

3

Sayyad shirazi Highway

Iran

Pullout

4

Sadeghiye

Iran

Pullout

5

Sharak gharb

Iran

Pullout

6

Pusan

South Korea

Pullout Numerical

7

Gyeonggi

South Korea

Pullout Numerical

The mechanical properties of soil such as cohesion, friction angle, elastic modulus, moisture content and percentage of coarse and finegrained soils were determined in the laboratory for Kharazmi university of Iran, while the data analysis and finalized result is performed in the Institute of geotechnical engineering (IGT) in Austria. The disturbed samples were used to determine the soil physical properties like particle size distribution. Test method for ParticleSize analysis of was succeeded according to the standard of [12]. The particle size graph shows in Fig. 1.
Fig. 1. Soil particle size dispersion graph for Tehran province sites
To evaluate the mechanical properties of the soil, the direct shear test is performed in the mentioned laboratory. The values of soil cohesion and fraction angle have been evaluated according to [13]. Standard method [14, 15] are also used to assess the moisture content and soil density respectively. The plate load test (PLT) has been performed to estimate the attribute values of soil elastic modulus (Fig. 2). Hence it is conducted regarding the standard method [16]. The achieved results of all laboratory and filed experimental works are reported in Table 2.
Fig. 2. In hole plate load test experiment to evaluate the insitu elastic modulus
Table 2. The mechanical properties of soil in different evaluated sites
Site No.

$\mathrm{\Phi}$
[Degree]

$C$
[kPa]

Elastic modulus
[kPa]

$\gamma $
[kN/m^{2}]

Moisture content
[%]

PI

LL

Ʋ

1

35

9

60000

20,6

9,52

7,5

25,5

0,32

2

33

49

35000

20

7,4

14,43

40

0,35

*3 (4 m)

45

2

35000

20

10,54

6,6

34,7

0,3

*3 (8 m)

45

1

48000

20

11,5

6,6

30

0,3

4

38

12

80000

21

7,6

4

23,8

0,33

5

33

7

65000

20,2

9,24

14,9

34,7

0,32

6

31

15,88

33320

16,66

N.D**

N.D

N.D

0,33

7

42

6

34370

17,67

N.D

N.D

N.D

0,3

* Depth of measurement
** Nondetected

The properties of nail bars that have been used in current study tests presented in Table 3. Two sizes of steel bars have been chosen 40 and 32 mm for both sites for Tehran and South Korea respectively (Fig. 3). The unbound length for all test is considered 1m and the length bounded skin has been reported in Table 3. In addition, the maximum grouting pressure in current work is chosen 200 and 500 kPa. The overburden load as the soil’s column height has been selected both 2 and 8 meters (Fig. 4). Furthermore, the diameter of nailing hole is considered 110 mm and 105 mm for experimental and reviewing work respectively.
Table 3. The nail rebar properties that used in this study
Site No.

$D$ [mm]

Elastic modulus [kPa]

Bond length [m]

Unbound length [m]

Max pressure [kPa]

Hole diameter [mm]

Overburden [m]

1

40

1,20E+10

3

1

200

110

4 and 8

2

40

1,20E+10

3

1

200

110

4 and 8

3

40

1,20E+10

3

1

200

110

4 and 8

4

40

1,20E+10

3

1

200

110

4 and 8

5

40

1,20E+10

3

1

200

110

4 and 8

6

32

2,00E+10

3

1

500

105

2

7

32

2,00E+10

3

1

500

105

2

The standard pullout test due to a Federal Highway Administration (FHWA) report, has been conducted in mentioned sites on the nonstructural nails for this destructive tests. Due to a FHWA report, a period of 7 days is needed to get the desired physical strength after grouting. In order to perform the test, an Enerpac 600 kN cylindrical hydraulic jack was used. The pressure gauge has been calibrated according to ISO 143904Ukas (England) (Ukas, 2006). The parts of the jack and its displacement and pressure gauge have been shown in Fig. 5.
Fig. 3. The steel bar that have been used in Tehran
Fig. 4. The facing for the nailed wall in site of Pasdaran, Tehran province
Fig. 5. Pullout test by using Enerpac 600 jack to pulling the rebar
The test has been carried out with constant force with 10 min rest time. During each stage of the experiment, the value of force increment has been increased 50 kN. The forcetime diagram related the site of Sayad Shirazi Highway is shown in Fig. 6.
Fig. 6. The ForceTime diagram for Sayad Shirazi Highway site considering 10 min rest
Results of pullout tests in due to two different type of gravity and pressure injection are presented in Fig. 8. It is observed that the maximum bound strength in case of gravity pressure would have occurred in both of Tajrish and Artesh sites that are located in the north of Tehran province. While bound strength for Pussan and Goenngy have shown higher range in the comparison with the mentioned sites in Tehran. In a detailed comparison, it is observed that some factors such as the soil mechanical properties, the hole diameter and the elastic modulus of bars would be affected by the bond strength.
In addition, the results of pressured injection pull out the test is reported on the right side of Fig. 7. The graph shows that in the case of pressure grouting, the response of bound strength for a nailing system significantly has been changed. In addition, it is observed that in case of pressure grouting, the response of bound strength in the site of Sadeghiyeh has been increased more than Tajrish site. However, once again both cases of Geoyongy and pussan are have been shown the highest response of shear bond strength.
Fig. 7. Results of pullout test of site: a) gravity grouting pressure, b) high pressure grouting pressure
a)
b)
The primary statistical analysis to determine the values of mean, median, standard errors and variance of soil domain has performed and its results are reported in Table 4. 223 different data have been extracted out from pullout tests to use as input for future development.
Table 4. Result of primary statistically analysis for evaluated soil
Statistically analysis type

Moisture content [%]

PI

LL

Elastic modulus [kN/m^{2}]

$\gamma $ [kN/m^{3}]

$\phi $

$C$
[kN/m^{2}]

$\omega $

$\vartheta $

Mean

9,07

9,17

32,39

5,25E+04

19,90

36,76

15,84

6,86

0,32

Median

9,24

7,50

34,70

4,80E+04

20,00

35,00

9,00

5,00

0,32

Std. error of mean

0,09

0,28

0,39

1,15E+03

0,08

0,31

1,12

0,29

0,00

Minimum

7,40

4,00

23,80

3,33E+04

16,66

31,00

1,00

3,00

0,30

Maximum

10,54

14,90

40,00

8,00E+04

21,00

45,00

49,00

15,00

0,35

Range

3,14

10,90

16,20

4,67E+04

4,34

14,00

48,00

12,00

0,05

Std. Deviation

1,27

4,21

5,83

1,72E+04

1,18

4,67

16,69

4,31

0,02

Variance

1,62

17,69

33,98

2,97E+08

1,39

21,77

278,70

18,60

0,00

To assess the correlation for each impressive factor on the shear strength and its relationship with soil nailing system displacement, a Pearson correlation (PC) test to determine the coefficient correlation has been conducted. Results of PC analysis showed that, the displacement values (Dis) strongly depended on the rate of moisture content (MC), soil specific weight ($\gamma $), bounded length of nails bar (BL), pullout shear stress (PSS), nail elastic modulus (NEM), hole diameter ($D$), grouting pressure (G.P) and overburdens length (OB). A number of parameters have had negative and others have had positive effects on the nailed system displacement. Furthermore, it is observed that PSS, BL, $D$, NEM, OB, GP, $\mathrm{{\rm Y}}$ and MC had the highest effect on the Dis respectively. The finalised PC values have been reported in Table 5.
Table 5. Results of Pearson correlation for soil measured data
MC

LL

SEM

$\gamma $

Ø

$C$

B.L

PSS

Dis

NEM

$\omega $

$D$

$\vartheta $

G.P

OB


MC

1

0.035

–.310

–.525

.466

0.718

–.475

–.190

–.136

.475

.533

–.475

–.788

.201

–.322

PI

–.298

.708

–.282

0.039

–.589

.556

.250

0.114

0.114

–.250

–.652

.250

.427

–0.105

.175

LL

1

–.792

–.433

–0.126

.529

–.163

0.017

0.069

.163

–0.126

–.163

.213

0.059

–0.11


SEM

1

.654

–0.078

–.408

.443

0.073

0.044

–.443

–0.119

.443

–0.058

–.172

.357


$\gamma $

1

0.05

0.007

.939

.287

.291

–.939

–0.12

.939

0.055

–.396

.649


Ø

1

–.536

–0.008

–0.006

0.058

0.008

.759

–0.008

–.787

0.005

–0.002


$C$

1

0.128

0.124

0.083

–0.128

–.507

0.128

.864

–0.066

0.078


B.L

1

.325

.371

–1.000

–0.068

1.000

0.121

–.433

.693


PSS

1

–.926

–.325

–0.023

.325

0.09

–0.1

.259


Dis

1

.371

0.104

.371

0.047

.241

.246


NEM

1

0.068

–1.000

–0.121

.433

–.693


$\omega $

1

–0.068

–.542

0.006

–0.043


$D$

1

0.121

–.433

.693


$\vartheta $

1

–0.065

0.077


G.P

1

–.288


OB

1

To complete the statistical analysis a hierarchical clustering (HCA) has been performed. The results of hierarchical clustering usually would be presented in a dendrogram. The group dendrogram for impressive factors illustrated in Fig. 8. It is observed that the relationship between the set of moisture content and pressure grout is more considerable than the relationship between the set of soil specific weight, hole diameter, and bound length. Besides, the dendrogram truly has been shown that the poison ratio would be depended to cohesion and dilation angle has a meaningful relationship with soil friction angle.
Fig. 8. The HCA dendrogram for nailing system specific groups
According to the results of PC and HCA analysis, the integral effective parameters for Disp had been selected. Hence, four different sets of input parameters are generated as the models in current work. A general and three special models (model 1 to model 3) to develop new practical relationships for estimating the “Disp.” have been considered. The constant condition for bounded length also had been considered in the current work. While the effects of G.P in case of the general model has been neglected. To consider the effects of G.P on the Disp, the model 1 have been generated. Also, other relationships that have focused to reduce inputs were also made as models 2 and 3. The effects of G.P neglected in model 2 while it has been considered in model 3. The input parameters for all of the developed models are shown in Table 6.
Table 6. Input parameters for each of generated model to develop new relations
General model

Model 1

Model 2

Model 3

M.C

M.C

M.C

M.C

PI

$\Upsilon $

$\Upsilon $

$\Upsilon $

S.E.M

N.E.M

Ø

Ø

$C$

Ø

$C$

$C$

G.P

C

P.S.S

P.S.S

P.S.S

P.S.S

O.B

O.B

O.B

O.B

$D$

D

$\omega $

$\omega $

G.P


$D$

$D$


$\vartheta $

G.P


N.E.M


Strain

The extracted results of displacement, bond strength and total strain for the nailing system have been evaluated by using the Kriging method. The total strain is consisting of elastic strain for steel bar, elastic strain for cement grout, elastic strain for soil and plastic strain. The primary estimation of the displacement and total strain of nailing system are performed by using Kriging method. The result of kriging prediction has been illustrated in Fig. 9. It is observed that the total strain has a semilinear behaviour considering the increase of shear stress.
Fig. 9. The kriging estimation of total strain considering pullout shear stress and displacement
Fig. 10. The kriging estimation of displacement considering pullout shear stress and grouting pressure
Displacement and bond strength has been directly estimated by using the Fig. 10 that generated by using the Kriging method. The grouting pressure effect on the shear strength has been illustrated in this figure. It is shown that in case of high bound strength by increasing the grouting pressure, the Disp would be reduced. While in case of weakly bound strength, the grouting pressure effects can be negligible.
Due to principal assumptions, to develop new relationships for finding the nailing system displacement, four different linear regressions had been conducted. The coefficient determination and standard error for the estimation have been reported in Table 7. The result of the general model shows that it has the fully linear behaviour by achieving the $R$ square 0.997. While the achieved results of Disp in the case of model 1 also show that considering grouting pressure effects the $R$ square coefficient would be reduced up to 9 percent. It means that the grouting pressure might become a nonlinear behaviour compares with gravity pressure. However, the outcome $R$ square in both cases of model 2 and 3 are lower than general model while both of them are reported extremely similar.
Table 7. Result of coefficient determination and error coefficient in developed models
Model

$R$ Square

Adjusted $R$ square

Std. error of the estimate

General

0.997

0.997

0.4704

1

0.911

0.907

2.65656

2

0.895

0.891

2.87263

3

0.910

0.907

2.66062

To develop relationship related to general model is driven as Eq. (1). It has 11 different parameters as inputs. While the measuring of someone of inputs such as total strain is not so easy. Hence this equation would be so used fully in case of verification:
To consider the effects of pressured grouting the relationship that related to model 2 is generated as Eq. (2). Hence it is able to consider pressure effect and removed the strain parameters. This equation is probably useful and practical while it has around 10 different input that they would become complicated to use in a relationship:
Due to the aim of current work and to use minimum input parameters for developing new practical relationships the following equations have been generated. Eq. (3) is able to estimate Disp without considering the grouting pressure and Eq. (4) is capable to estimate Disp considering grouting pressure as well:
The extracted results of the general model and experimental pullout tests have been shown in Fig. 11. The reasonable result has been observed due to use this verification. Hence negligible overestimation results would be occurred by using the Eq. (1).
Fig. 11. Comparison results of new developed relation for general model and experimental work
Results for estimation capability for Eq. (2) that has used to consider grouting effect is also illustrated in Fig. 12. It is observed that the effect of grouting pressure in the collaboration for estimating the Disp would have decreases role in a comparison with gravity grouting cases. While considering the pressure effect may decrease the normal linear behaviour for Disp and it may be changed to nonlinear behaviour. Hence, the G.P effects can increase the estimation error. Results showed that in case of higher pressure grouting the error for estimation would be increased while in case of lower pressure it has a reasonable estimation. Therefore, it is recommended to use the Eq. (2) for estimating just in grouting pressure values lower than 500 kPa.
Fig. 12. Comparison results of new developed relation for model 1 and experimental work
Fig. 13. Results of linear regression for model 2 and experimental work
Results of two practical developed relationships (Eq. (3) and Eq. (4) are also shown in Fig. 13 and Fig. 14. With an emphasis on gravity pressure, it is observed that the estimated values by using the Eq. (3) a good estimation for displacement in a compare with extracted results of experimental work would be illustrated. Figures show that in the last part of each relation estimation the maximum error to estimate the displacement would occur. The local result of coefficient determination is near 0.85. The main reason of this weakly estimation is outcome regarding the difference in injection pressure and nail elastic modulus. Hence it would have resulted that mentioned relationships have an excellent estimation in case of grouting pressure lower than 500 kPa and normal elastic modulus for bars.
Fig. 14. Results of linear regression for model 3 and experimental work
A multilayer neural network is generated to verify the results of model 2 and 3. A one hidden layer neural network by using the hyperbolic tangent for activation has been considered to estimate the Disp. In addition, 8 different input factors for two cases of neural network have been used and have reported in Table 8. Furthermore, 221 different data are used as neural network’s input parameters. 70 percent of input data have been used for training step and others used for test step in neural network processing. The identity function is also used for the output activation function. Finally, the Sum of Squares has been chosen for error investigating in the network structure. The generated structure of the neural network in the current study has been shown in Table 8.
Table 8. Structure of input, hidden and output layer of neural network
Input layer

Factors

M.C


$\Upsilon $


Ø


$C$


P.S.S


O.B


$D$


G.P*


Hidden layer(s)

Number of units

62


Number of hidden layers

1


Number of units in hidden layer 1a

2


Activation function

Hyperbolic tangent


Output layer

Dependent variables

1

Displacement

Number of units

1


Rescaling method for scale dependents

Standardized


Activation function

Identity


Error function

Sum of Squares


* G.P is used just in Neural network model 2

The results of neural network predicting for both generated neural networks are reported in Fig. 15 and Fig. 16. The coefficient determination for the first neural network is found 0.95. The mentioned coefficient for the second model of neural network (G.P effect) is also reported 0.91. It is observed that the neural network has a good estimation in case of highpressure grouting and high range of nail elastic modulus.
Fig. 15. Comparison results of neural network (Model 1) and experimental work to estimate of displacement
Fig. 16. Comparison results of neural network (Model 2) and experimental work to estimate of displacement
Results for each conducted analysis in this work are shown in Fig. 17. It has been observed that the maximum error occurred in case of linear regressions (L.R) models that have estimated around 10 percent. However, in case of highpressure the neural network has done better estimation in a compare with the L.R. Due to all of the achieved results it would be recommended to use the linear regressions in case of gravity pressure or pressure grouting not more than 300 kPa and normal stiffness steel. Moreover, in case of highly pressured grouting and stiff nail bar the generated neural network in current work would be able to excellent estimate the Disp.
Fig. 17. Complete comparison for all analysis during current study
To show comparison results separately, the achieved results of developed relationships, neural network experimental pullout test have been plotted in Figs. 18 to 21. The nonlinear estimation of neural network has been illustrated in mentioned figures.
Fig. 18. Results of displacement estimation in site of Gyeonggi: a) displacement estimation in case of high grouting pressure [500 kPa]; b) displacement estimation in case of gravity pressure grouting
a)
b)
Fig. 19. Results of displacement estimation in site of Shahrak gharb: a) displacement estimation in case of gravity pressure grouting and 4 meters of O.B; b): displacement estimation in case of high grouting pressure [200 kPa] and 4 meter O.B.
a)
b)
Fig. 20. Results of displacement estimation in site of Shahrak gharb: a) displacement estimation in case of gravity pressure grouting and 8 meters of O.B; b) displacement estimation in case of high grouting pressure [200 kPa] and 8 meter O.B.
a)
b)
Fig. 21. Results of displacement estimation in site of Artesh: a) displacement estimation in case of high grouting pressure [200 kPa] and 8 meters of O.B; b) displacement estimation in case of gravity pressure grouting and 8 meter O.B.
a)
b)
The sensitivity analysis for the rate of important parameters has been performed. Related results are also shown in Fig. 22. It is observed that in case of pressure grouting the degree of importance of P.S.S will decrease compared with gravity pressure cases. While in case of pressure grouting the O.B and hole diameter have considerable effects compare with the results of gravity grouting. Furthermore, the result shows that in nonpressure grouting, the soil mechanical properties have a significant effect to decrease the displacement. However, in case of pressured grouting, the effective parameters have been changed. Parameters O.B, D, and $\gamma $ have an integral role to estimate the nailing system displacement compare with their role in gravity grouting.
Fig. 22. The values of importance factor in case of a) pressure grouting and b) gravity grouting
a)
b)
The number of the experimental pullout test has been done and their results are used as input data to develop the new relationship for estimating the displacement of a nailing system. The standard procedures of the pullout test have been performed in five different sites in Tehran, Iran. Moreover, results of a previous experimental work are chosen as additional data. Furthermore, new relationships to consider the grouting pressure effect on displacement has been considered. New relationships for both cases of gravity and pressured grouting has been developed. The following Conclusions are extracted from current research:
1) The two times increasing in G.P can increase the pullout shear stress maximum to three times. It means the grouting pressure maximum to 600 kPa would be increase the bond strength to three time greater compare with gravity grouting conditions.
2) Results of developed relationships showed that the general relationship is able to estimate displacement with lowest error and determination coefficient 0.99. Hence it is so useful for verification. Furthermore, results of other models have had determination coefficient among 0.89 to 0.91. The result of this relation showed that dependency of bound skin fraction to other significant gravity grouting factors could be linear. However, in case of pressure grouting, the dependency is changed to nonlinear.
3) Achieved results showed the linear regressions have good estimating for displacement considering gravity and pressure grouting not more than 300 kPa. In case of higher pressure grouting and high stiffness steel bar, the recommends neural network would be more capable of better estimation compare with linear regression.
4) Maximum importance factor related to input considered in both case of gravity and pressured grouting is reported by P.S.S. achieved result show that the soil mechanical property is the major factor which has significant effect on nailing system displacement. Parameters $\gamma $ and moisture content have secondary powerful effects upon nailing system displacement. In case of pressured grouting the pattern of s importance factor for parameters will be changed. The effects of $D$ and O.B will be increased until 3 times.
The authors wish to appreciate the institute of geotechnical engineering, University of Bodenkultur, Vienna, Austria, for their generous supports to complete this work.