Geotechnical Testing Journal, Vol. 28, No. 1Paper ID GTJ12312

Available online at: www.astm.org

Dar-Hao Chen,1 Deng-Fong Lin,2 Pen-Hwang Liau,3 and John Bilyeu4

A Correlation Between Dynamic ConePenetrometer Values and Pavement Layer Moduli

ABSTRACT: The Dynamic Cone Penetrometer (DCP) is one of the least expensive testing devices able to characterize base and subgrade properties.To fully use the DCP in pavement evaluation, an empirical relationship between DCP penetration rate and layer modulus is required. However, theliterature on this correlation is limited. This study incorporates a total of 198 DCP and Falling Weight Deflectometer (FWD) tests done over 8 yearson various types of highways (Interstate Highway, US, and Farm-to-Market). The computer program MODULUS was employed to backcalculatethe layer moduli from the FWD results to build a correlation with DCP results. A comparison was made with the widely-used model by Powell et al.(1984). It is found that the difference between the two models decreases as the Penetration Rate (PR) increases. For a PR of less than 10 mm/blow,the difference between these two models was over 10 %. The difference is only about 1.7 % when the PR is 80 mm/blow. Without knowing the truemoduli, it is impossible to tell which equation is better. The correlation developed here provides another option and allows researchers to recognizethe range of variability.

KEYWORDS: dynamic cone penetrometer (DCP), falling weight deflectometer (FWD), correlation

Introduction

Although in pavement design the moduli are used to determinethe required layer thickness(es) of a pavement structure, density andmoisture content are the two parameters for project acceptance.Density and modulus are very different material characteristics,even though density may be a good indicator of the strength ofgranular materials (Chen et al. 1999B; Livneh and Goldberg 2001).There is a clear gap between design and construction. District designand construction engineers often wonder what are the constructedbase and subgrade moduli. The goal of lower cost and improvedquality demands more precise quality control and quality assurance(QC/QA) programs that tie test results into design practice, makingthe in-place measurement of design parameters, like stiffness andmodulus, necessary. Rapid in-situ stiffness/modulus testing wouldmake it easier for transportation agencies to conduct reliable anddefensible quality assurance programs.

Currently there is no standard field test to determine the resilientmodulus of base and subgrade soils for construction quality con-trol/assurance purposes; though many transportation agencies arecollecting stiffness/modulus along with density and moisture mea-surement. The Falling Weight Deflectometer (FWD), Geogauge,Dirt Seismic Pavement Analyzer (DSPA), and laboratory repeti-tive triaxial tests have been used to determine the pavement layermodulus (Nazarian et al. 2002; Livneh and Goldberg 2001; Rahim

Received November 3, 2003; accepted for publication June 7, 2004; publishedJanuary 2005.

1 APT System Manager, Construction Division, Texas Department of Trans-portation, 4203 Bull Creek #39, Austin, TX 78731, dchen@dot.state.tx.us.

2 Associate Professor, Department of Civil Engineering, I-Shou University,1, Section 1, Hsueh-Cheng Rd. Ta-Hsu Hsiang, Kaohsiung County, 84008,Taiwan. dflin@isu.edu.tw.

3 Associate Professor, Department of Mathematics, National Kaohsiung Nor-mal University, Kaohsiung 802, Taiwan, R.O.C. phliau@nknucc.nknu.edu.tw.

4 Transportation Engineer, Construction Division, Texas Department ofTransportation, 4203 Bull Creek #39, Austin, TX 78731, jbilyeu@dot.state.tx.us.

and George 2002; Sawangsuriya et al. 2002). However, the lim-itations of each method are equally real. As many different setsof layer moduli would satisfy the same FWD deflection bowl,practicing pavement engineers struggle to identify the correct set.Also, the FWD often is unable to determine the extent of a weakbase/subgrade layer due to a thick concrete layer that carries mostof the load away. Laboratory repetitive triaxial tests are seldomused to determine the layer moduli for routine design or QC/QAtests in current DOT environments (Rahim and George 2002; Chenet al. 2001b). Seismic tests are quick and easy, but the seismi-cally determined modulus is very high due to the high frequenciesand miniscule loads used. The Geogauge shows some promise,but is highly sensitive to the surface preparation, and it only givesa composite stiffness that includes all layers to some uncertaindepth.

The Dynamic Cone Penetrometer (DCP) has become a cost-saving alternative for characterizing the properties of pavementlayers without digging test pits or collecting soil samples. TheDCP serves as an excellent tool for construction inspection; it hasthe ability to verify both the level and uniformity of compaction(Burnham 1996; Siekmeier et al. 1999). In addition, the layer thick-ness can be determined from the changing slope of the depth versusaccumulated blows profile. The DCP is an excellent tool to charac-terize base/subgrade properties under problematic jointed concretepavements where there are voids or weak layers. Also, the DCPis useful when the backcalculated moduli from the FWD data isin question, such as when the asphalt concrete (AC) thickness isless than 75 mm (3 in.), or when shallow bedrock is present. Inaddition, it is fairly easy to collect and analyze DCP data. The DCPhas not been widely used in the pavement engineering community,partly due to the lack of a solid correlation between DCP resultsand modulus values. Before the DCP can evaluate layer stiffness, anempirical correlation needs to be established. Many equations havebeen proposed to correlate DCP results to California Bearing Ratio(CBR) values. However, there are not many studies devoted to thecorrelation of CBR values to moduli or DCP results to moduli.

42 Copyright © 2005 by ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959.

CHEN ET AL. ON PAVEMENT LAYER MODULI 43

FIG. 1—DCP and FWD test sites.

The goal of this study is to develop an equation to estimatemodulus through DCP testing. 198 DCP tests have been conductedon various highway classifications [Interstate Highway (IH), US,Farm-to-Market (FM)]. FWD tests were conducted before the DCPtests, at the same location, to determine the layer moduli throughbackcalculation. About 20 % of DCP tests were from the MobileLoad Simulator (MLS) project. The MLS is a full scale, acceleratedpavement testing (APT) device. Under the MLS project, FWD,laboratory, Spectral Analysis of Surface Waves (SASW), and in-situinstrumentation results are available for comparison. This increasesthe confidence in the analysis results (Chen and Hugo 1998; Chenet al. 1999a; Chen and Hugo, 2001). The other 80 % of the testswere conducted for forensic or special study projects over an 8-yearperiod. Some of those results have been documented in literature(Chen et al. 2001b; Chen et al. 2002; Chen et al. 2003).

Test Sections

Figure 1 and Table 1 depict the test sites and pavement structure[asphalt concrete (AC) surface and granular base thickness]. Asindicated in Table 1, numerous tests were conducted at each testsite at different locations with minimum spacing of 1.5 m. Forsome test sites, the spacing was as much as 30 m between the test

TABLE 1—Test site descriptions.

AC Thickness Base ThicknessLocation (mm) (mm) # Tests

IH35 on top of base 0 356 3US290 on top of base 0 356 5FM1644 13 305 8US290/281 51 305 15US82WB 51 254 24US82EB 51 254 2FM740 76 254 5US281SB (FortWorth) 89 254 2US83 102 203 5IH35 on top of 4′′AC 102 356 7FM2818 102 305 31FM2818 102 152 12IH635FR 102 610 21US281 (SPS1) 127 305 13IH30 178 203 11US290 178 127 5US281SB (MLS) 203 381 24US281NB (MLS) 203 381 5Total 198

locations. Some of the tests were conducted on top of the base layerduring construction (e.g., IH35 and US290). There were four testsites on US281 in different parts of the state.

After one year of trafficking, severe alligator cracking and deeprutting were found in a foamed-asphalt project on US82, as shownin Fig. 2. Extensive field tests, including FWD, SPA, Ground Pen-etration Radar (GPR), and DCP, were conducted to investigate thecause of structural distress. Laboratory tests also were done to de-termine gradation, moisture content, capillary action, and indirecttensile strength. Four trenches were opened to test each layer di-rectly and to obtain samples for laboratory testing. It was foundthat the subgrade modulus in the failed areas was similar to thatin the intact areas. The foamed-asphalt base moduli on the intactareas were approximately 5–8 times higher than in the failed area.It was concluded that the rutting and alligator cracking were asso-ciated with failure of the foamed asphalt base. The foamed asphaltbase exhibited a severe loss of strength when subjected to moisture(Chen et al. 2004a).

A significant amount (∼20 %) of the DCP and FWD resultsused in this study were from the MLS project on US281, which hadwell-known pavement performance and extensive test results (Chenand Hugo 1998; Chen and Hugo 2001; Chen et al. 2001b). Layermoduli from FWD, laboratory triaxial, SASW, and in-situ instru-mentation results are available for comparison, which increases the

FIG. 2—DCP and FWD tests on US82 (a forensic study on a premature failure site).

44 GEOTECHNICAL TESTING JOURNAL

FIG. 3—DCP (left) and FWD tests (right) on FM1644 before the 1 million lb superheavy load move.

confidence of using those data. US281 is a two-lane highway (ineach direction, a total of four lanes) in the Fort Worth District withan average of 3100 vehicles per day (1550 per direction) in 1994.Accelerated pavement testing was applied on southbound (SB) andnorthbound (NB) lanes of US281 to determine the effectiveness ofthe rehabilitation treatments. Approximately 972 000 and 388 800of 80 kN Equivalent Single Axle Loads (ESAL) were applied bythe Texas MLS to the SB and NB lanes, respectively. After 972 000and 388 800 ESALs, the average ruts were 4.31 mm and 10.11 mm,respectively. The 972 000 ESAL is equivalent to 8 years of traffic,which is the minimum life required by the FHWA for a rehabili-tation work. The rehabilitation strategy used in the SB lanes wassuperior to the NB lanes for rutting resistance. Rutting was theprimary distress mode.

The DCP and FWD were applied to three job sites in the DallasDistrict (IH635FR, FM 2818, IH30) and one site in the AustinDistrict (US290) (Chen et al. 2001a). These four projects werechemically treated with liquid stabilizers. TxDOT occasionally hasto look for alternatives to lime stabilization because sulfates in thesoil would otherwise cause heaving problems. In these projects,the effectiveness of chemical treatments was evaluated by stiffnessmeasurements of the stabilized layers and adjacent non-stabilizedlayers.

Two sections of US290 were tested with the DCP and FWD. Bothsections consist of 51 mm of AC over 305 mm of crushed limestonebase. The only difference between these two sections is that thebase of the first section was treated with EN1 liquid stabilizer. Thepavement structure of the frontage road (FR) IH635FR consistsof a 102 mm AC on top of 610 mm of liquid-stabilized (EMCsquared/EMS) subgrade. The IH30 pavement consists of 178 mmof AC and 203 mm of EMC Squared/EMS treated subgrade. TheFM2818 pavement structure also has 102 mm of AC. DCP andFWD tests were conducted on two sections of FM2818. The firstpavement section included 102 mm of AC over 305 mm of subgrademodified with EMC Squared/EMS. This section was constructedon approximately 4.57 m (15 ft) of fill material. Approximately3.04 m (10 ft) down within the fill materials there is another 305 mmof subgrade modified with EMC Squared/EMS. The second sectionof FM2818 included 102 mm of HMAC over 152 mm of subgradetreated with EMC Squared/EMS.

FM1644 is a load-zoned road with a Gross Vehicle Weight(GVW) restriction of 26 520 kg (58 420 lb). Two requests foridentical superheavy loads slightly over 454 000 kg (1 million lb)were permitted on load-zoned road FM1644. This was to transporttwo generators for a power plant (Chen et al. 2004b). Before thesuperheavy load move, DCP, FWD, and other tests were per-

formed to improve the understanding of pavement behavior underthese conditions, as shown in Fig. 3. The maximum deflections ofFM1644 for a 40 kN load are in the range of 40–60 mils (1.02–1.52 mm). Note that typical deflections for an interstate highwayare in the range of 2–8 mils (0.05–0.20 mm). No visible damagewas observed after the moves, even though the pavement structurewas weak.

The SPS1 pavement test sections on US281 (US281-SPS1 inTable 1) in south Texas is the largest Long Term Pavement Perfor-mance (LTPP) experimental site in the US. The project was openedto traffic in 1997, and pavement performance has been poor. Threeof these test sections developed deep rutting within one year. Theirsurfaces were milled to restore the ride quality. Three years afterconstruction, 14 of the sections had 10 mm or more rutting. Aforensic study was initiated by TxDOT to identify the cause ofthe problem (Chen et al. 2003). Nondestructive testing (FWD andGPR) and destructive field investigation was initiated, as shown inFig. 4. The original plan was to cut nine trenches. However, afterfour trenches were cut, the problematic layer was identified, andthe trenching operation was terminated. DCP, stiffness gauge, seis-mic pavement analyzer, and nuclear density gauge tests were thenconducted on top of the base and subgrade layers.

Hot mix asphalt industries have been promoting a heavy dutyand long lasting asphalt pavement called perpetual pavements. Per-petual pavements use multiple layers of durable asphalt to producea smooth, long-lasting road. TxDOT is experimenting with perpet-ual pavement on IH35, one of the most heavily trafficked routes inTexas. DCP, FWD, and other tests were conducted on top of the356 mm base and after placement of 102 mm of asphalt, as indicatedin Table 1. It is important to note that when DCP tests were con-ducted on top of asphalt, 19 mm holes were drilled to enable testing.

Existing Correlation Equations

Currently, there are no direct correlation equations between DCPpenetration and modulus values. However, there are equations tocorrelate DCP penetration and CBR values. For example, the U.S.Army Corps of Engineers found a relationship for a wide range ofgranular and cohesive materials, as given in Eq 1 (Webster et al.1992). Equation 1 has been adopted by many researchers and prac-titioners (Livneh 1995; Webster et al. 1992, Siekmeier et al. 1999).

log CBR = 2.465 − 1.12 (log PR) or CBR = 292/PR1.12 (1)

where:CBR = California Bearing Ratio, andPR = the DCP’s penetration through the layer in units of mm/blow.

CHEN ET AL. ON PAVEMENT LAYER MODULI 45

FIG. 4—DCP, FWD, and other tests on US281 and US290 (forensic studies on premature failure sites).

Although the 1993 AASHTO Guide for Design of PavementStructures adopted Eq 2 for calculating moduli (E) through CBR,the equation is only a rough estimate, as the moduli from which thiscorrelation was developed ranged from 750–3000 × the CBR value.Also, the formula is limited to fine-grained soils with a soaked CBRof 10 or less.

E(psi) = 1500 ∗ CBR or E(MPa) = 10.34 ∗ CBR (2)

The most widely accepted relationship between CBR and mod-ulus (Eq 3) was proposed by Powell et al. (1984).

E(psi) = 2550 ∗ CBR0.64 or E(MPa) = 17.58 ∗ CBR0.64 (3)

Combining Eq 1 and Eq 3, a direct relationship betweenDCP penetration and modulus value can be established, as givenin Eq 4:

E(ksi) = 96.468 ∗ PR−0.7168 or E(MPa) = 664.67 ∗ PR−0.7168

(4)

Correlation Equation Developed in This Study

Data Preparation

The MODULUS program developed by the Texas TransportationInstitute (Uzan et al. 1988) was employed to backcalculate the layermoduli from FWD results. This program normally does not yieldreasonable estimates of layer moduli when the AC thickness is lessthan 75 mm (3 in.). In this case (or if there is no AC at all), theprogram BISAR was used, iteratively, to find a set of layer moduliwhere all deflections, measured on the surface by the FWD and atdepth by multi-depth deflectometers, will match.

It is reported by Livneh et al. (1995) and Chen et al. (2001a) thatthe DCP results are affected by the test procedure; that is, thereis at least a 10 % difference in penetration rate when tests are runthrough a hole drilled in the AC, as opposed to tests done directlyon base without AC overburden pressure. Factors were proposedby those two studies (Livneh et al. 1995; Chen et al. 2001a) tocorrelate the results conducted directly on top of the base to thosethrough a drilled hole. In the present study, the factors proposedby Chen et al. (2001a) were adopted with factors 1.19 and 1.12 forbase and subgrade layers, respectively.

DCPunc = 1.19 DCPcon for base (5)

DCPunc = 1.12 DCPcon for subgrade (6)

whereDCPunc = test on top of base (mm/blow), andDCPcon = test on top of AC through a narrow drilled hole (mm/blow).

There were two sites (IH35 and US290) where the DCP and FWDtests were conducted on top of the base. The data collections weremade immediately after the base construction. Thus, the factors of1.19 and 1.12 were applied to base and subgrade for these two sites.The combined IH35 and US290 data made up approximately 10 %of the overall data population. A slight reduction in data scatterwas found by applying the correction factors. The improvementwas because only small portions of the DCP tests were con-ducted directly on top of the base. The authors believe that thecorrection factor impact will be greater when the population sizeincreases.

46 GEOTECHNICAL TESTING JOURNAL

FIG. 5—Determination of normal distribution.

Regression Analysis

Equation 4 was selected as the basic model for this study. Equa-tion 4 is a linear equation that can be expressed in log form tofacilitate a regression analysis:

Log (EMPa) = a − b ∗ Log (PR) (7)

where a and b are the regression coefficients. After applying Eq. 7,the “mean shift outlier model” by Sanford Weisberg (1985) wasused for outlier detection. When the highest residual was deter-mined to be an outlier, it was removed from the data set, and theremaining data were passed through the algorithm again. The pro-cess continues until no outlier can be found in the data set. Afterthis procedure was complete, 227 data points remained; 119 in baseand 108 in subgrade. Therefore, only approximately 60 % of thedata (119 out of 198) was selected for model development becausethe outliers are expected for the DCP tests. Sometimes the DCPtip will encounter large aggregate or cobblestones that will skewthe results. There are numerous instances where the FWD deflec-tions are similar (e.g., less than 20 %) at the same test site, butthe PR values vary by more than 400 %. It should be noted thatnot all of the remaining 119 bases have the subgrade PR results.There were 11 locations (119–108) without subgrade PR valuesbecause the DCP tests were only conducted on the base layer. Thiswas because the base was too hard to penetrate, and tests wereterminated before reaching the subgrade.

The two basic assumptions for a linear regression analysis are:1) the data are normally distributed, and 2) the data are random.Typically, with sufficient data (like this study), it is reasonable toassume a normal distribution. An effort was made to determine ifthe data used in this study are really normal distribution. A straightline on the probability versus residual plot is a good indication of anormal distribution. As shown in Fig. 5, the line is nearly straight,and the p-value is 0.072. This means that under the null hypothesisand at a certain tolerance level (alpha = 0.05), the hypothesis wasnot rejected. Thus, the data used in this study are indeed a normaldistribution.

In general, for a large data set, the normal distribution assump-tion is not a concern; rather, the randomness and constant varianceassumption is more risky. Efforts were made to verify this assump-tion. As shown in Fig. 6, the residuals were spread almost equallyabove and below the zero line (x-axis), which is a good indicationthat the data set has the properties of randomness and constant vari-ance. Note that fitted values and residuals in Fig. 6 are the results ofthe regression on the log (E MPa) and log (PR) data. Thus, the 227data set is not only normally distributed but also has the propertiesof randomness and constant variance.

Table 2 presents the results of the ANOVA analyses performedon the 227 data set. The derived equation is presented in Eq 8.The R2 was found be 0.855, which could also be obtained by197.05/230.47, as shown in Table 2. The corrected sum of squares(SS), which measures the total variability in the observations, was230.47. And the amount of variability in the observation was dividedinto two components. One was accounted for by the regression linewith variability of 197.05. The other one, residual variation leftunexplained by the regression line, was 33.42. As shown in Table 2,the standard error of the coefficient of log (PR) was 0.01824, andthe T (–36.42) was obtained by 0.66453/0.01824. The statisticaltest confirmed that the p-value of the variable log (PR) was lessthan 0.1 %. This indicates that this term was very significant andhas a strong ability to explain the model variations. On the otherhand, the same result could be obtained by examining the F value(–36.422 = 1326.7 = 197.05/0.15). Furthermore, the standard errorof the observation was estimated by 0.3854 = (0.15)1/2.

E(ksi) = 78.05 ∗ PR−0.6645 or E(MPa ) = 537.76 ∗ PR−0.6645,

R2 = 0.855, MSE = 0.15 (8)

where E is young’s modulus, and PR is the penetration rate of theDCP in mm/blow.

Figure 7 shows the comparisons between the field test results(DCP mm/blow and FWD moduli) and the model from Eq 8. Aneffort was made to compare Eq 4 and Eq 8, and the results arepresented in Fig. 8, which indicates that themoduli from these two

CHEN ET AL. ON PAVEMENT LAYER MODULI 47

TABLE 2—ANOVA analyses on the log (EMPa) and log (PR) data.

Predictor Coef SE Coef T Source DF SS MS F

Constant 4.3574 0.0405 107.51 Regression 1 197.05 197.05 1326.7∗log(PR) −0.66453 0.01824 −36.42† Residual Error 225 33.42 0.15

S = 0.3854 R-Sq = 85.5 % R-Sq (adj) = 85.4 % Total 226b 230.47

∗Significant at 0.1 %.†Degree of Freedom (DF) is 226 for a 227 data set.

FIG. 6—Determination of randomness and constant variance.

FIG. 7—Correlation between field DCP (PR) and FWD moduli.

FIG. 8—Comparison of the models (Chen, Eq 4 & Powel, Eq 8).

48 GEOTECHNICAL TESTING JOURNAL

equations increase as the PR decreases. For example, when the PRis 1 mm per blow, Eq 4 and Eq 8 yield modulus values of 665 and538 MPa, respectively. This is a difference of 24 % of the Eq 8result. When the PR is 10 mm per blow, the results from Eqs 4 and 8are 128 and 116 MPa, a difference of only 9.6 % of the Eq 8 result.This difference crosses through zero at about 57 mm/blow and is–1.7 % when the PR increases to 80 mm per blow. Thus, it indicatesthat the main difference between this study and the model by Powellet al. (1984) is when the PR is small. Based on field DCP tests, it isalso observed that the variability among DCP results increases asthe PR decreases. Without ground-truth moduli, we are unable todifferentiate which equation is more accurate. Equation 8 providesanother option and allows researchers to recognize the range of vari-ability. It is important to note that there is a limited number of equa-tions to determine the modulus through CBR or PR, and the mostwidely accepted relationship between CBR and modulus (Eq 3)was proposed by Powell et al. in 1984. The FWD was not yetwidely used in 1984.

Conclusion

It is well known that it is time-consuming and costly to repairproblems caused by an inferior base or subgrade. For the purposesof quality control/assurance and for tying test results into designpractice, a technique that can provide the stiffness/modulus of thepavement layer is a rational choice. DCPs have been used by severalagencies with much success. To fully use the DCP in pavementevaluation, an empirical relationship with layer moduli is required.Over an 8-year period, 198 DCP and FWD tests were conductedon different roadways in Texas. Some of the tests were conductedduring construction, that is, before the AC placement. On the basisof the results obtained, the following conclusions were drawn:

� There are only a few equations to correlate DCP penetrationrate and modulus.

� A correlation between DCP penetration rate and modulus wasdeveloped successfully in this study. The equation can be usedfor both base and subgrade soils.

� An effort was made to compare the model developed in thisstudy with that by Powell et al. The difference between thesetwo models increases as the PR decreases. For a PR of lessthan 10 mm/blow, the difference between these two modelswas over 10 %. The difference is only about 1.7 % when thePR is 80 mm/blow.

� The correlation equation developed in this study provides analternative for researchers and practitioners. It allows them torecognize the range of the variability.

Acknowledgments

This work could not have been completed without the assistanceof Mr. Ralph Self, Mr. Carlos Peralez, Mr. Billy Pigg, Ms. DarleneGoehl, Mr. Cy Helms, Mr. Randy Beck, Mr. Norman Erickson,Mr. Magdy Mikhail, Mr. Bill Willeford, Dr. Andrew Wimsatt, andDr. Mike Murphy of TxDOT.

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