a field study of in situ california bearing ratio and

Australian Road Research 13(4), December 1983, pp. 2 8 5-94.

A Field Study of In Situ California Bearing Ratio and Dynamic Cone Penetrometer Testing for Road

Subgrade Investigations

R.B. SMITH Senior Scientific Officer.

Department of Main Roads, P.O. Box 240, Parramatta, N.S.W. 2150.

D.N. PRATT Investigations Officer,

Department of Main Roads, P.O. Box 198, Haymarket, N.S.W. 2000.

ABSTRACT

Field tests were carried out to determine the repeatability of results obtained from both the in situ

California Bearing Ratio (CBR) test and the Scala dynamic cone penetrometer, and the correla-tion between results of both tests. Testing was carried out under field conditions so results are

those expected under such conditions rather than under ideal laboratory-type' conditions. The

materials tested consisted of a subgrade of mottled clay in which iron nodules had developed and an imported subgrade of yellow clay with sandstone nodules. Results indicated that the coeffi-

cient of variation of a CBR for the particular material at one test location could be of the order of 60 per cent whilst that of the cone penetrometer could be of the order of 40 per cent. The correla-tion between the two tests was found to be best represented by an inverse relationship. It was also

found that, for the material tested, in situ results were generally lower than those obtained in the

laboratory from samples compacted at field moisture content and density.

Introduction

With the trend away from empirical methods of pave-ment design based on classification test data, there has been increased interest in California Bearing Ratio (CBR) testing. Much of the CBR testing is laboratory oriented but in situ testing is becoming more widespread. This paper describes an investigation used to evaluate the in situ CBR and the dynamic cone penetrometer (DCP) tests.

Literature Review

Very little appears to have been written on the correla-tion between dynamic cone penetrometer (DCP) test results and in situ CBR results.

Key (1964) compared in situ CBR results and a static cone penetrometer developed by the United Kingdom Military Engineering Experimental Establish-ment. He concluded that on a uniform heavy clay soil, in the range of CBR between 2 to 15, the penetrometer

ACKNOWLEDGEMENT

The authors wish to thank the Commissioner for Main Roads,

Mr B.N. Loder, for permission to publish this paper. The opi-nions expressed are those of the authors and not necessarily

those of the Department of Main Roads, New South Wales.

Australian Road Research, 13(4), December 1983

(with direct CBR reading) and the normal in situ CBR equipment would give the same results. Sanglerat (1972) in his review only cited the work of the Australian, Scala, in respect of research into the correlation between in situ CBR results and cone penetrometer test results.

It appears that such investigations are not routinely carried out in France (Sanglerat 1976; Lareal, Sanglerat and Geilly 1976). de Garidel-Thoron and Javor (1983) reported on the recent development in France of a small dynamic penetrometer to estimate CBR value. In Belgium a dynamic core penetrometer has been developed in which a 10 kg drop hammer is dropped 50 cm (Centre de Recherches, Routieres 1980). The Belgian workers found that their apparatus was only suited to soil ranging from silt to fine sandy soils. They found that with the relationship

log CBR = —1.31 log (mm/blow) + 2.58

the 95 per cent confidence interval is situated between 0.70 and 1.40 times the calculated value. Schmertmann (1978) in his review only referred to correlations bet-ween in situ CBR and the static cone penetrometer. It would appear, however, that most of the work in Australia is based on and follows the work of Scala (1956).

Scala developed a dynamic cone and then carried out correlation studies between the in situ CBR and his DCP, and between the in situ CBR and the static cone penetrometer. The DCP developed by Scala has a point

285

SMITH, PRATT -ROAD SUBGR ADE INVESTIGATIONS

angle of 30°, a cross-sectional area at its greatest width of 322 mm' (1/2 sq. in), and a drop mass of 9.08 kg (20 Ib) falling 508 mm (20 in). With metrication the various States in Australia have adopted slightly different dimensions and tolerances.

The Scala cone penetrometer was modified and simplified by van Vuuren (1969) in Zimbabwe who con-cluded that the correlation between his cone and in situ CBR 'is remarkably good and that the difference in CBR results obtained by the two different approaches was usually only a few CBR' (p. 854).

In Australia, much of the work performed to deter-mine the correlation between the in situ CBR procedure and the Scala DCP has accepted the premise that only one in situ CBR test site is necessary. Scala (1956) noted that serious discrepancies were sometimes encountered between results of duplicate tests but this comment does not appear to have been heeded by later researchers. For instance, Morris (1976) and Morris, Potter and Armstrong (1977) apparently based their correlations on a single in situ CBR value per site.

This paper is an extension of the work described by Smith (1983).

Testing Details

Testing was performed on both the subgrade and im-ported subgrade of an experimental pavement at Plumpton on the western outskirts of Sydney. The subgrade consisted of mottled clay in which iron nodules had developed whilst the imported subgrade consisted of yellow clay with sandstone nodules. Average results of classification tests for each layer are given in Table I.

Data were collected under field conditions which meant that work had to be carried out accurately but speedily. Results represent, therefore, what could be ex-pected under field conditions rather than under ideal laboratory-type' conditions.

1st Phase In the first phase of the investigation, 30 test sites were excavated in the existing pavement to the approximate finished subgrade level. The excavations were approx-imately 1 m2 in area. At each site three in situ CBR tests were carried out in a line at approximately 150 mm spac-ings. Three sand replacement density in situ tests were performed adjacent to the CBR sites and material was excavated for laboratory CBR testing. The test pro-cedures are described in Department of Main Roads, N.S.W. (DMR) (1975). Testing was performed im-mediately after excavation of the test site. The results are given in Table II.

2nd Phase The second phase, carried out during construction, con-sisted of in situ CBR (DMR Test Method T118) and cone penetrometer testing (DMR Test Method T161). Testing was carried out just prior to the addition of material for the next layer (i.e. generally the day after the respective layer had been compacted and shaped). Compaction was generally between 95 and 100 per cent standard. The results are given in Tables III and IV.

Three in situ CBR tests were again carried out at each selected site in a line at 150 mm spacing on the compacted surface of the layer. Moisture contents were taken from the layer 50 mm to 150 mm below the com-pacted surface at each penetration site. Tests were car-ried out at the same site for each layer.

The DCP tests were carried out on the surface of the imported subgrade. Three penetrations were made ap-proximately 1 m apart to form a triangle with the in situ CBR test location as the centroid. For the imported subgrade the number of blows to drive the penetrometer 50 mm into the surface was taken as the reading (see Table IV). The imported subgrade was 200 mm thick. For the subgrade, therefore, the relevant penetration figure was that which occurred at approximately 250 mm below the surface level (see Table III). Change of layer

TABLE I

Properties of Materials

Test Property

Subgrade Imported Subgrade

Mean t Standard

Deviation

Mean t Standard

Deviation

T106 Material retained on 19.0 mm sieve (%) 1.21 1.63 4.23 4.39

T106 Material passing 9.5 mm sieve* (%) 97.21 1.66 97.53 1.85

Material passing 4.75 mm sieve* (%) 88.23 4.65 95.00 2.39

Material passing 2.36 mm sieve* (%) 77.03 9.09 92.37 2.54

T107 Material passing 425 gm sieve** (%) 90.76 4.81 92.00 1.41

Material passing 75 gm sieve** (%) 73.28 8.14 51.40 2.43

Material less than 13.5 gm** (%) 48.03 8.17 36.90 2.60

TIO8 Liquid Limit 39.29 7.06 38.48 3.59

T109 Plastic Limit 16.29 3.15 13.82 1.55

TI13 Linear Shrinkage (%) 11.05 2.63 8.37 2.24

T1 1 1 Maximum dry density (t/m 3) 1.88 0.09 1.90 0.03

Optimum moisture content (%) 14.90 1.96 13.03 0.96

Expressed as percentage of material passing 19.0 mm sieve

** Expressed as percentage of material passing 2.36 mm sieve

t Recorded to 2 decimal places for statistical purposes only •

286 Australian Road Research, 13(4), December 1983

SMITH, PRATT-ROAD SUBGR ADE INVESTIGATIONS

TABLE II

Dry Density CBR and Moisture Content Results: Subgrade Prior to Reconstruction

Dry Density In Situ CBR (tIm3) (%)

Moisture Content Immediately Under

CBR (%)

Site Mean sd CV Mean sd CV

Mean sd CV

1 1.73 0.08 4.62 7.73 3.73 48.25 14.23 1.10 7.73

2 1.87 0.04 2.14 16.00 3.46 21.63 13.70 0.00

3 1.96 0.05 2.55 15.67 2.52 16.08 13.10 1.39 10.30

4 1.96 0.14 7.14 10.53 2.54 24.12 13.20 1.49 11.29

5 1.80 0.09 5.00 14.67 16.79 114.45 13.77 1.17 8.50

6 1.86 0.10 5.38 14.83 8.10 54.62 15.37 0.35 2.28

7 1.83 0.11 6.01 9.83 1.26 12.82 16.13 0.29 1.80

8 1.95 0.11 5.64 4.53 1.67 36.87 14.63 1.29 8.82

9 2.14 0.10 4.67 29.33 12.22 41.66 15.10 2.72 18.01

10 1.98 0.05 2.53 18.77 9.94 52.96 16.30 7.14 43.80

11 1.72 0.04 2.33 21.67 2.08 9.60 9.63 0.47 4.88

12 2.00 0.06 3.00 40.67 1.53 3.76 7.40 0.17 2.30

13 1.84 0.07 3.80 58.33 2.52 4.32 7.30 1.30 17.81

14 2.05 0.04 1.95 22.67 4.51 19.89 8.47 0.75 8.85

15 1.83 0.02 1.09 39.33 4.04 10.27 10.50 1.10 10.48

16 1.65 0.05 3.03 8.73 1.63 18.67 17.87 1.12 6.27

17 1.98 0.03 1.52 19.67 0.58 2.95 11.33 0.15 1.32

18 2.18 0.04 1.83 53.67 2.08 3.88 6.30 0.10 1.59

19 1.80 0.04 2.22 22.00 1.00 4.55 12.60 0.61 4.84

20 1.86 0.03 1.61 12.67 1.53 12.08 11.97 1.36 11.36

21 1.99 0.05 2.51 18.67 0.58 3.11 13.67 1.00 7.32

22 1.92 0.05 2.60 56.33 5.03 8.93 9.50 1.18 12.42

23 1.95 0.07 2.59 22.00 1.73 7.86 8.67 0.25 2.88

24 2.10 0.04 1.90 58.33 4.04 6.93 5.77 1.53 26.52

25 2.00 0.08 4.00 37.00 1.73 4.68 5.57 1.12 20.11

26 1.83 0.03 1.64 33.67 4.73 14.05 9.27 1.48 15.97

27 1.60 0.04 2.50 11.67 0.58 4.97 20.93 1.89 9.03

28 1.74 0.03 1.72 8.87 1.00 11.27 14.37 2.34 16.28

29 1.78 0.03 1.69 24.67 1.15 4.66 15.37 2.64 17.18

30 1.68 0.05 2.98 10.63 1.58 14.86 12.80 1.56 12.19

was readily detected and the rate of penetration re-mained fairly constant for up to 100 mm past that point. Close level control meant that surface irregularities could be readily taken into consideration. Analyses were carried out separately for each of the two materials.

Test Results

For experimental purposes each CBR was recorded to the nearest 0.1 per cent for all values under 20. All moisture contents were calculated to the nearest 0.1 per cent. As is the custom, DCP readings were calculated to the nearest 0.1 blows/25 mm. For statistical purposes the figures in Tables 11 and /// are given to the nearest 0.01.

From Tables II , III and IV it can be seen that the results are quite variable. Such variation would be ex-pected between sites because of different levels of com-paction, moisture content and material quality. The coefficients of variation (CVs) were calculated for each property for the sets of three results at each site and rele-vant comparisons were made.

As can be seen from Table V , it could be expected that in 95 per cent of cases the CV for CBR test results would be less than 60 per cent in the case of the subgrade, both before and after reconstruction, and 50 per cent in the case of the imported subgrade. For the DCP, in 95 per cent of cases the CV would be less than 40 per cent in the case of the imported subgrade and 31 per cent in the case of the subgrade.


CVs were used to decribe variation of testing. Variation within a site was in many instances as great as overall variation. Such variation would mask the action and interaction of variables and therefore an analysis of variation was not undertaken. Table VI details the various correlation coefficients for CBR test data.

An ersatz analysis involved testing whether the CVs of CBR values were dependent on moisture con-tents and density.

For the subgrade before reconstruction the CV of CBR was dependent on the mean CBR (r = -0.35), and also CV and mean of dry density (r = 0.48) at 0.05 level. Note that this was the only case where density tests were performed.

None of the other correlation coefficients were sig-nificant. It is suggested, therefore, that for the sites tested CBR results may be density rather than moisture dependent.

The degree of compaction at each test site would have been fairly uniform but the results could be depen-dent on the material properties. It is possible that the variable results were caused by large particles just under the piston during testing or due to other material varia-tion. The CV of the in situ CBR test is also dependent on inherent variability of the test. For instance, Blakeley (1965) has shown that laboratory CBR is dependent on the moisture content at compaction and the curing con-ditions prior to penetration. Also, the field equipment is subject to more variation than laboratory equipment. At

287

SMITH, PRATT - ROAD SUBGR ADE INVESTIGATIONS

TABLE III

CBR, Moisture Content and Penetration Results: Material 1 -Subgrade

Mean

CBR (%)

sd CV Mean

Moisture Content (%)

sd CV Mean

Penetration (Blows12.5 min)

sd CV

20.33 2.57 12.64 18.40 0.50 2.72 2.53 0.70 27.67 12.0 1.73 14.42 15.37 2.11 13.37 2.70 1.25 46.30 12.33 4.04 32.77 17.93 2.00 11.15 1.47 0.42 28.57 8.23 4.65 56.50 14.73 5.39 36.59 0.57 0.05 8.77

17.67 6.51 36.84 18.53 1.79 9.66 1.67 0.52 31.14 34.67 10.07 29.05 8.10 1.90 23.46 1.87 0.29 15.51 44.67 7.51 16.81 11.73 2.75 23.44 6.57 1.33 20.24 19.33 8.74 45.21 17.47 0.51 2.92 2.33 N = 1 21.67 1.53 7.06 16.43 1.27 7.73 1.87 0.45 24.06 55.0 4.36 7.93 12.63 1.10 8.71 2.47 0.29 11,.W4 49.0 10.39 21.20 14.33 0.57 3.98 2.6 N = 1 37.67 6.66 17.68 13.23 0.29 2.19 2.53 0.92 36.36 59.0 31.95 54.15 10.57 0.64 6.05 4.17 0.33 7.91 78.67 17.61 22.38 10.73 1.57 14.63 3.57 0.86 24.09

135.67 9.02 6.65 12.87 3.42 26.57 3.97 0.78 19.65 55.67 1.53 2.75 10.00 0.43 4.30 3.60 1.04 28.89 34.67 23.00 66.34 10.93 1.36 12.44 4.57 0.31 6.78 13.0 2.65 20.38 8.57 1.50 17.50 2.03 0.37 18.23 32.33 4.62 14.29 16.53 4.33 26.19 5.87 0.79 13.46 41.0 1.73 4.22 8.37 0.35 4.18 4.70 0.81 17.23 41.0 25.71 62.71 9.13 1.72 18.84 5.17 0.86 16.63 18.33 2.31 12..60 10.97 2.48 22.61 4.50 0.14 3.11 88.00 38.97 44.28 13.47 6.62 49.15 8.33 1.67 20.05 32.67 2.52 7.71 10.93 0.21 1.92 5.37 2.37 44.13 5.67 1.98 34.92 10.07 1.97 19.56 3.37 0.83 24.63 1.10 0.30 27.27 11.83 3.26 27.56 1.67 0.38 22.75 3.35 14.10 2.20 0.65 29.55 2.23 1.20 53.81 17.63 1.75 9.93 2.50 0.78 31.20 3.97 1.95 49.12 9.10 0.10 1.10 3.17 0.26 8.20 1.43 1.06 74.13 15.43 2.55 16.53 1.80 0.14 7.78

65.67 20.21 30.78 17.47 0.55 3.15 39.00 18.08 46.36 16.00 0.52 3.25 19.67 1.53 7.78 10.07 1.97 19.56 12.00 3.00 25.00 19.07 1.19 6.24 24.67 6.81 27.60 16.30 1.57 9.63

times most of the effort is taken in causing the truck springs to expand, lifting the body away from the ground rather than penetrating the soil. Also, the truck is on the point of equilibrium with its springs, meaning that the truck is susceptible to wind and traffic motion. The penetration rate becomes somewhat variable. It is reasonable to expect, therefore, that in extremely varia-ble materials the CVs would be higher.

In the case of the DCP the test sites were approx-imately 1 in apart. In this case the material variability would have caused at least some of the variance because the penetrometer readings were taken at approximately I m from each other at the test site. Under more variable conditions higher CVs might be expected. In each case the CVs of tests carried out on the imported subgrade were less than those of tests carried out on the subgrade. This is consistent with the classification test data given in Table I where the CVs of the test data were lower for the selected subgrade than for the subgrade for material passing the 19 mm sieve.

Relationship Between CBR and DCP Data

DCP data were expressed in the usual units of mm/blow. Data were analysed using SPSS Program REGRESSION

288

(Kim and Kohout 1975) separately for the mean CBR and mean penetration of the subgrade, imported subgrade, and for combined results. The data given by Scala (1956) were also analysed separately and combined with the current data.

A variety of regressions was attempted. The highest correlation coefficients were achieved with log/log and inverse relationships. The results of all data, including that of Scala, together with the regression line are shown in Fig. I.

The log/log regression is:

log (CBR) - 1.145 log (PENETRATION) + 2.555

(mm/blow)

The inverse regression equation is:

322.097 CBR = - 1.738 PENETRATION

Results from the Rooty Hill trial conform to a log/log relationship as proposed by Scala (1956).

Inverse relationships gave better correlation for Rooty Hill data (r = 0.78 cf. 0.60). A good case is not made, however, to contradict the earlier work as the log/log relationship gives a better fit for the combined data (r = 0.85 cf. 0.77 for the inverse relationship).



TABLE IV CBR, Moisture Content and Penetration Results:

Material 2 - Imported Subgrade

Mean

CBR (%)

sd CV Mean

Moisture Content (%)

sd CV Mean

Penetration (Blows/15 mm)

sd CV

47.00 7.94 16.89 12.70 0.20 1.57 2.77 0.56 20.22

48.67 15.31 31.46 10.40 0.10 0.96 2.35 0.93 29.57

21.67 1.16 5.35 13.53 0.65 4.80 1.77 0.33 18.64

33.67 5.77 17.14 11.07 0.60 5.42 2.03 0.05 2.46

22.00 4.58 20.82 10.27 0.55 5.36 1.40 0.14 10.00

25.00 2.65 10.60 13.30 1.65 12.41 25.67 2.89 11.26 14.00 1.01 7.21 2.30 0.05 2.17

36.00 2.00 5.56 8.33 0.97 11.64 36.67 3.06 8.34 8.07 0.23 2.85 1.82 0.52 28.57

80.33 10.69 13.31 9.00 6.73 4.18 62.11

53.00 5.20 9.81 8.37 1.70 20.31 130.50 8.90 0.20 2.25 123.33 1.53 1.24 8.23 0.72 8.75 4.10 2.30 56.10

90.33 27.15 30.06 9.93 1.06 10.67 5.43 1.45 26.70

148.67 15.95 10.73 6.20 0.30 4.84 53.33 32.04 60.08 9.17 0.84 9.16

198.67 12.59 6.34 5.10 2.25 44.12 6.9 N = 1

157.50 6.80 0.46 6.76 8.90 0.53 5.96

107.00 52.83 44.37 8.43 0.21 2.49 8.40 0.83 9.88

263.00 6.60 0.52 7.88 22.13 4.78 21.60

150.33 72.23 48.05 7.03 0.61 8.68 45.67 10.79 23.63 10.93 0.06 0.55 76.33 11.59 15.18 11.27 0.85 7.54 83.33 3.22 3.86 10.13 1.36 13.43 3.33 0.62 18.62 47.30 36.88 77.97 7.73 2.72 35.19 4.60 0.32 6.96 56.33 3.51 6.23 11.70 0.92 7.86 54.33 7.10 13.07 9.83 0.25 2.54 2.40 0.45 18.75 57.33 15.31 26.71 8.07 3.44 42.63 3.10 0.65 20.97 40.00 9.54 23.85 12.17 0.31 2.55 4.90 0.29 5.92 42.67 2.08 4.87 12.53 1.00 7.98 2.27 0.54 23.79 41.33 17.10 41.37 11.80 0.75 6.36 2.00 0.62 31.00 28.00 2.65 9.46 12.23 0.25 2.04 2.70 0.49 18.15 14.67 1.16 7.91 11.47 1.17 10.20 3.03 0.89 29.37 39.67 2.08 5.24 11.04 0.77 6.96 4.43 0.33 7.45 36.67 15.14 41.29 11.00 1.05 9.55 4.97 0.56 11.27 28.67 6.11 21.31 11.50 1.51 13.13 2.03 0.05 2.46 41.33 2.31 5.59 12.43 0.51 4.10 1.90 0.45 23.68 28.33 5.51 19.45 11.87 0.49 4.13 2.17 0.09 4.15 32.00 2.00 6.25 11.77 0.05 0.42 2.63 0.38 14.45 34.00 15.59 45.85 10.53 0.64 6.08 3.77 1.26 33.42 42.33 14.43 34.09 10.17 0.25 2.46 3.13 0.76 24.28 72.33 0.58 0.80 10.27 0.95 9.25 3.00 0.93 31.00

TABLE V Coefficients of Variation

at Various Percentiles

Coefficient of Variation Material Test

50th 95th Percentile Percentile

Subgrade prior to reconstruction CBR 15 58

Subgrade after CBR 27 57 compaction Penetrometer 23 31

Imported subgrade CBR 13 48 after compaction Penetrometer 20 40

Good correlation indicates that two different methods of testing are measuring essentially the same material property. A coefficient of 0.85 is quite en-couraging for a material as variable as soil.

Presentation of a regression equation naturally leads to the temptation to translate results of one test to


the other. Such practice could lead to quite consistent er-rors for a particular material type or condition that may not have been adequately represented in the original work.

If a correlation were to be obtained for each material a large number of sites per material is required and the

289

CBR (%)


TABLE VI

Correlation Coefficients for CBR Test Data

Material

Property

Subgrade

Subgrade

Imported beibre

after

Siebgrade ReconsmIction

Compaction

alter

Compaction

CV of CBR versus CV of moisture content

top 30 mm under piston 0.12

CV of CBR versus mean moisture content

top 30 mm under piston 0.23

CV of CBR versus CV of moisture content

50 mm to 150 mm below piston 0.13 0.18

CV of CBR versus mean moisture content

50 mm to 150 mm below piston 0.24 0.10

CV of CBR versus mean CBR -0.35 -0.24 -0.01

CV of CBR versus CV of dry density 0.48

Mean CBR versus mean dry density 0.48

200.0

180.0

160.0

140.0

120.0

100.0

80.0

• . 2 •

3 • • • 2•

40.0 .2 2 •2 22 ** 032 2 5 oe 2 3

32 • 500. •

• 2.632 • •

2 2 712 • 2510-5_3_1D._ •

• • 95

2 2 2

•

log (CBR) = - 1.145 log (PENETRATION) + 2.555

(mm/blow)

(r = 0.85)

• • 5 5 • 3

60.0

20.0

0.0 00

10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0 160.0

Penetration mm/blow

Fig. 1 -CBR v. penetration

time taken to perform the study would be high com-pared to the benefits. The time would be better spent ob-taining additional cone penetrometer results at addi-tional sites. Hence the adoption of an acceptable rela-tionship is justified. Such adoption should not reduce the time spent obtaining information. The cone penetrometer provides information for several layers at once. Many sites can generally be tested in the time taken to perform the required number of CBR tests on various layers at one site.

As the experimental pavement consisted of six dis-tinct sections, analyses were performed to determine the effect of the adoption of the inverse relationship on the CBR value for the in situ subgrade and imported subgrade in each section. Data are given in Table VII.

Results in Table V// give the 10th percentile CBR values from in situ CBR testing using the standard method of analysis (i.e. using mean of three results).

290

Each individual CBR test result at the site and cone penetrometer result (average of three) are converted to CBR values. Because the cone penetrometer results were some distance from each other it was considered that the mean value was the most appropriate value to adopt in that case.

It can be seen that none of the three methods of reducing results yields a consistently lower figure than the other two methods. Whilst it may be appropriate to take the mean in situ CBR value at a site as a reasonable assessment of the CBR at that site, it would appear to be more appropriate to use individual figures and obtain the 10th percentile value from these to determine the repre-sentative CBR for a section. This is particularly the case where individual results can be affected by a stone under the piston and the like.

In seven cases the 10th percentile CBR determined from individual results was lower than that for the 10th


SMITH, PRATT—ROAD SUBGR ADE INVESTIGATIONS

TABLE VII

10th Percentile CBR Values for Each Section and Layer Determined from Mean In Situ CBR Value per Site, Individual Values of In Situ CBR, and Cone Penetrometer Results

Section Layer 10th Percentile

Mean CBR

10th Percentile Individual

CBR

CBR.from Cone

Penetrometer

Subgrade Imported Subgrade

12 21

13 21

19 15

2 Subgrade 8 13 6

Imported Subgrade 36 36 24

3 Subgrade 12 15 19


4 Subgrade 53 34 16


5 Subgrade 13 17 26 Imported Subgrade 14 16 22

6 Subgrade 1.1 1.1 17


percentile from mean results. In five cases the reverse was true.

In Section 6 where in situ CBR values were very low the cone penetrometer grossly over-estimated the CBR using the inverse relationship. The reason is unclear but the subgrade in Section 6 was soft, wet and spongy when tested by in situ CBR and may have been more fully compacted and may have dried out during placement of the imported subgrade. Also, cone penetrometer read-ings are taken when the cone has penetrated approx-imately 50 mm whereas in situ CBR results are taken at a penetration of 2.5 mm. This means that in situ CBR is more susceptible to water on the surface. Section 6 was inundated but surface dry just prior to CBR testing. It was apparent from the surface that a calculated CBR of 17 from penetrometer readings was unrealistically high.

Overall the cone penetrometer gave results as ac-ceptable as the in situ CBR. Certainly if the time taken to undertake in situ CBR testing had been applied to addi-tional cone penetrometer testing the derived CBR results would show more clearly the variation one would expect in a section of pavement.

Because'of the variability in results from in situ CBR testing, it is considered that for pavement design pur-poses the cone penetrometer test is just as acceptable as the in situ CBR.

Relationship Between In Situ CBR and Laboratory CBR Compacted at

Field Moisture and Density

As mentioned earlier, samples of subgrade were taken prior to compaction to determine laboratory CBR values at field moisture content and density. The specimens were prepared in duplicate. Field density and moisture contents were determined from samples obtained during density in situ testing. Where the moisture content or density varied at the site, either the mean value or the more common value was adopted if two results were similar and one different. The moisture content of the


sample was adjusted to the required moisture content and allowed to cure. The material was placed in a mould in three equal layers, each layer being compacted using dynamic compaction such that the overall density re-quired was achieved. A combination of compaction by a standard rammer and a Kango hammer was used.

Results were analysed using a t-test for paired results and a correlation coefficient. This analysis was done to assure that duplicate sampling, and testing, would produce consistent (repeatable) results. A high correlation was indicated between each piece of data per pair (Table VIII ). There was no significant difference overall between pairs of data with the moisture content (t = 0.52) being more uniform than the dry density at compaction (t = 1.14) which in turn was more uniform than the CBR (t = 1.90). Nevertheless, correlation bet-ween pairs of data was highest for the CBR. This means that whilst there was some variation within pairs of data the overall ranking of results was similar. Mean results for each pair of data are given in Table VIII.

The relationship between in situ CBR and laborato-ry CBR is shown in Fig. 2. A correlation coefficient of 0.65 was calculated.

However, a correlation coefficient of 0.83 was achieved by arbitrary exclusion of the two pairs of data, circled on Fig. 2. The degree of correlation was not im-proved, however, by the exclusion of data where mean field dry density and mean laboratory density showed gross variations.

Regression equations for these data were mislead-ing. Fig. 2 shows a scattering of points. For example, a remoulded CBR of around 30 could be seen to corres-pond to an in situ CBR of between about 12 and 32 or possibly up to 58. This is consistent with results reported by Black (1961) where there was wide variation between the two methods.

Black (1961) considered the variation to be due to different porewater pressures affecting test results. Also, the confining effect of the rigid mould in laboratory tests tended to yield higher laboratory results, especially for granular soils. In addition, there was variation between

291

SMITH, PRATT -ROAD SUBGR ADE INVESTIGATIONS

TABLE VIII

Mean Dry Densities, Moisture Contents and CBR Values for Pairs of CBR Specimens Compacted at Field Moisture Content and Density

Site Thy Density

(tIrn-9

Moisture Content

(%)

CBR

(%)

1 1.72 16.40 9.35 2 1.84 15.05 2.20

3 1.94 13.90 28.00 4 1.95 14.60 19.00

5 1.79 16.80 9.05

6 1.75 15.20 2.70

7 1.81 16.60 3.50

8 1.96 12.50 9.60

9 2.14 11.50 23.50

10 1.99 14.60 1.10

11 1.75 9.20 22.50

12 2.00 4.90 74.50

13 1.85 8.30 28.00

14 2.03 8.30 97.50

15 1.82 10.60 48.50

16 1.65 19.00 6.05

17 2.01 10.70 18.00

18 2.20 6.10 145.00

19 1.80 14.20 28.00

20 1.85 13.10 10.50

21 2.04 12.90 31.50

22 1.92 10.30 23.50

23 2.01 9.90 53.50

24 2.09 6.70 108.50

25 2.01 6.70 59.50

26 1.86 10.30 35.00

27 1.62 13.50 28.00

28 1.76 11.10 16.50

29 1.80 11.20 29.00

30 1.71 12.90 9.20

Paired t = 1.14

Paired t = 0.52

Paired t = 1.90 r = 0.963

r = 0.955

r = 0.976

so

54

48

42

In-situ CBR 36

(%)

30

24

18

12

6

O 0

0

15

30

45

60

75

90

105

120

135

150

Laboratory CBR (%)

Fig. 2 -In situ CBR v. laboratory values


SMITH, PRATT—ROAD SUBGRADE INVESTIGATIONS

the moisture and density values at the actual site of each CBR penetration and those adopted for laboratory test-ing. Whilst there was a degree of variation in moisture content and density, a higher laboratory moisture con-tent did not necessarily yield a laboratory CBR lower than the in situ CBR for a given dry density or vice versa. It would appear that porewater pressures and the confin-ing effect of the mould were more important than the moisture content and density at compaction in yielding laboratory CBR values higher than the in situ figures. In addition, the material in the field was probably rolled at above the optimum moisture content for the plant used whereas the laboratory samples were compacted at less than optimum moisture content. As mentioned earlier, Blakely (1965) has shown that the laboratory CBR is de-pendent on the moisture content and the curing condi-tions prior to compaction. There is no reason to expect that this does not also apply to the field situation.

Where it is intended that pavement thickness design be by means of the CBR, due attention should be paid to the fact that CBR specimens tested in the laboratory, after being prepared at field moisture content and density, tend to give higher CBR values than those which would be obtained in situ. This factor may be specific to certain materials. The materials used in this study were clays with hard nodules of sandstone or ironstone. In such cases, laboratory testing of such sam-ples should be discouraged and field testing performed. For reasons set out in the previous section, field testing should consist of a considerable number of cone penetrometer results rather than a few in situ CBR results.

Conclusion

Results indicate that the CV in CBR for a particular material at one test location could be of the order of 60 per cent whilst that of the cone penetrometer could be of the order of 40 per cent. An inverse relationship pro-vided the best correlation between the tests for the materials tested. In view of this the authors propose that cone penetrometer testing be performed in preference to in situ CBR testing.

The CBR values on material moulded at field moisture content and density give values which are generally higher than in situ CBR results. The authors consider that in situ testing should be carried out in preference to remoulding the samples at field moisture content and density. Again, the cone penetrometer is preferred.

REFERENCES

BLACK, W.P.M. (1961). The calculation of laboratory and in

situ values of California bearing ratio from bearing capacity

data. Geotechnique 11(1), pp. 14-21.

BLAKELEY, J.P. (1965). The California Bearing Ratio test on loess. Road Res. Unit, Bull. 2, Nat. Roads Board, N.Z.

CENTRE DE RECHERCHES ROUTIERES (1980). Light per- cussion sounding apparatus. C.R.R. leaflet A25.

de GARIDEL-THORON, R. and JAVOR, E. (1983). Un petit penetrometre dynamique pour evaluer l'indice C.B.R. Proc. Int. Symp. Soil and Rock Investigations by In Situ Testing, Paris, Vol. 2, pp. 43-47.

DEPARTMENT OF MAIN ROADS, NEW SOUTH WALES (1975 as amended). Materials testing manual. Volume 1: Soils aggregate concrete.

KEY, J.W. (1964). An investigation to compare in situ CBR values measured on a heavy clay with a prototype cone penetrometer against those obtained with a standard ap-paratus. Dept Sci. Industrial Res. Road Res. Lab. Lab. Note LN/682/JWK, October.

KIM, J.O. and KOHOUT, F.J. (1975). Multiple regression analysis: subprogram REGRESSION; In N.H. Nie, C.H. Hull, J.G. Jenkins, K. Steinbrenner and D.H. Bent. SPSS Statistical Package for the Social Sciences'. 2nd Ed. (McGraw-Hill: New York), pp. 320-67.

LAREAL, P., SANGLERAT, G. and GIELLY, J. (1976). Com-parison des essais de penetration effectues avec differents penetrometres statiques ou dynamiques. Annales de L'Institut Technique du Batiment et des Travaux Public, 340, pp. 15-24, June.

MORRIS, P.O. (1976). Studies into the construction of low trafficked roads in the City of Salisbury, South Australia. Australian Road Research Board. Research Report, ARR No. 58.

— POTTER, D.W. and ARMSTRONG, P. (1977). Assess-ment of subgrade moisture content and strength condi-tions in the Shire of Yalloroi. Australian Road Research Board. Internal Report, AIR 230-3.

SANGLERAT, G. (1972). The Penetrometer and Soil Exploration Interpretation of Nnetration Diagrams. Theory and Practice. (Elsevier: Amsterdam.)

— (1976). La Penetration en France. Rapport general. An-nales de L'Institut Technique du Batiment et des Travaux Public, 340, pp. 5-14, June.

SCALA, A.J. (1956). Simple methods of flexible pavement design using cone penetrometers. N.Z. Eng. 11(2), pp. 34-44.

SCHMERTMANN, J.H. (1978). Guidelines for cone penetrometer test performance and design. Final Report. U.S. Fed. Highw. Admin.

SMITH, R.B. (1983). In situ CBR and dynamic cone penetrometer testing. Proc. Int. Symp. Soil and Rock In-vestigations by In Situ Testing, Paris, Vol. 2, pp. 149-54.

van VUUREN, D.J. (1969). Rapid determination of CBR with the dynamic cone penetrometer. Rhodesian Eng. Paper 105, pp. 852-54, September.

Australian Road Research, 13(4), December 1983 293

R.B. SMITH,

SMITH, PRATT—ROAD SUBGR ADE INVESTIGATIONS

Robert Smith is a Senior Scientific Officer with the Department of Main Roads, N.S. W. On leaving school he became a Science Trainee with the Department and completed his Bachelor of Science degree at the University of Sydney in 1968. He then served in Broken Hill and Glen limes Divisional Laboratories. In 1974 lie was granted leave to undertake the Master of Education Course at the University of New England and was awarded the

B.Sc., M.Ed.(Hons) Master of Education degree in 1975. Further correspondence studies continued and he was awarded a further Master of Education degree with First Class Honours in 1983. He is presently under-taking the Master of Engineering Science Course at the University of New South Wales. Since February 1983 lie has been located at Parramatta Divisional Office where his duties include testing and evaluation of data from the Rooty Hill field trial. In relation to his work, Mr Smith has published papers on sampling and testing of road-making materials.

David Pratt completed his Bachelor of Science degree at the University of New South Wales in 1975. In the same year he joined the Department of Main Roads to work in that Department's Material and Research Section. He completed the Gra-duate Diploma in Data Processing cou►se at the New South Wales Institute of Tech-nology in 1981. As Investigations Officer his duties include planning statistical pro-cedures related to the testing of road building materials, and the design of com-puter programs for the storage and analysis of data.

D.N. PRATT, B.Sc.


a field study of in situ california bearing ratio and

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