RESILIENT MODULUS PROPERTIES OF TYPICAL GRANULAR BASE MATERIALS OF ONTARIO

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1 RESILIENT MODULUS PROPERTIES OF TYPICAL GRANULAR BASE MATERIALS OF ONTARIO D. F. E. Stolle, Department of Civil Engineering, McMaster University, Hamilton, Ontario, Canada P. Guo, Department of Civil Engineering, McMaster University, Hamilton, Ontario, Canada Y. Liu, Department of Civil Engineering, McMaster University, Hamilton, Ontario, Canada ABSTRACT For the design of flexible pavement structures, an essential component of the AASHTO 22 Design Guide is the use of the resilient moduli for base/subbase materials and subgrade soils. Before the design guide is adopted for Ontario, benchmark resilient moduli of typical unbound materials from across province are required to calibrate the AASHTO procedures taking into account soils and aggregates commonly encountered in Ontario. This study reports on resilient modulus test results for unbound pavement materials that were obtained according to AASHTO Standard T Of the 23 representative aggregates from across Ontario that were investigated, this paper focuses on relation of M r to confining pressure, as well as the sensitivity of M r to moulding water content for 5 of the 23 aggregates. RÉSUMÉ Pour le dimensionnement de structures de pavement flexibles, une composante essentielle du Guide AASHTO 22 est l utilisation du «resilient moduli» pour les matériaux de base et de sous base et les sols de soubassement. Avant l adoption du Guide pour l Ontario, des données de référence du «resilient moduli» de différents matériaux à travers la province sont nécessaires pour la calibration de la procédure AASHTO en tenant compte des sols et agrégats communément disponibles en Ontario. Cette étude rapporte les résultats de test du «resilient modulus» pour les matériaux de pavement qui ont été obtenus selon le Standard AASHTO T Parmi les 23 types d agrégats représentatifs en Ontario qui ont été étudiés, cet article se concentre sur la relation entre M r et la pression de confinement, et aussi sur la sensibilité de M r par rapport à la teneur en eau pour 5 des 23 agrégats. 1. INTRODUCTION Design of pavement structures in the past have been largely empirical in nature, relying heavily on the experience gained from studying the performance of pavements in road tests during the 195 s and early 196 s. More recently, the National Cooperative Highway Research Program (NCHRP) completed its development of the mechanistic-empirical procedures for flexible pavement design, which are expected to provide many improvements over the largely empirical AASHTO (American Association of State Highway and Transportation Officials) design guide currently in use; namely, AASHTO 1993 Pavement Design Guide. Based on better characterization of pavement materials and appropriate consideration of environmental effects, the newly developed design procedure is expected to improve design reliability and yield more cost-effective pavement designs. An essential component of the new more rational design procedure - AASHTO 22- is the use of the resilient moduli (M r) to characterize the material stiffness of base/subbase materials and subgrade soils. The Province of Ontario is currently in the process of moving from the use of AASHTO 1993 to AASHTO 22. Before the newer guideline is adopted for Ontario, benchmark resilient moduli of typical unbound materials from across the province are being determined to calibrate the procedures taking into account subgrade soils and aggregates commonly encountered in Ontario. This study determined representative resilient moduli for commercially available unbound base/subbase aggregates from the five regions of MTO. The following tasks define the work performed to accomplish the goals of the study: Task 1: Complete a literature review that focuses on the-state-of-the-art laboratory resilient modulus testing methods and findings, including the analysis of available data in Ontario. Task 2: Select with member(s) of the Ministry representative aggregates from each MTO region, taking into account whether the material is a Granular A or B, natural or manufactured (crushed stone) aggregate. Task 3: Perform a series of tests, including sieve analysis, Proctor compaction and California Bearing Ratio (CBR) tests, to identify the physical and index properties of each material. Task 4: Carry out resilient modulus tests, following the AASHTO Standard T37-99, on the aggregates at three moisture contents; i.e., the optimum moisture content and the optimum moisture content ±2%. Task 5: Analyze experimental data to establish a database, cataloguing the physical and index properties as well as the resilient modulus of each material. 236

2 This paper reports on a segment of the study that was completed, considering only 5 of the 23 aggregates investigated, and examining the use of linear empirical correlations between M r and average confining stress, as well as the moisture sensitivity of M r to moisture content. 2. LITERATURE REVIEW 2.1 Background Owing to our better understanding of the interaction among traffic loading, the environmental and pavement layer characteristics, the specifications for materials and tests to evaluate their suitability for use within a pavement structure have in more recent years become more sophisticated. Paralleling this evolution, the design methods have gradually evolved from empirical and semiempirical procedures relying on experience and the use of indices such as the CBR toward rational or mechanistic-based procedures, which require improved material characterization that takes into account the low stress levels relative to failure and repetitive loading. The resilient modulus M r is used for this purpose. M r testing provides a means of characterizing pavement construction materials, including subgrade soils, under a variety of conditions (i.e. moisture, density, temperature, etc) and stress states that simulate the conditions in a pavement subjected to moving wheel loads. Numerous studies have been performed with respect to resilient modulus testing, including, the seminal research in Ontario completed by Lam (1982). Experience has shown that M r testing is a complex and difficult task, which is reflected by the large variation in experimental results that has been observed among different test methods and testing laboratories; see, e.g., Barksdale et al. (1997). This is attributed to the many factors that have an effect on the measured resilient modulus of soils. Consequently, careful consideration of testing equipment, specimen preparation (including compaction method, density and moisture content control) is required to obtain laboratory test results that are consistent with those values encountered in the field. Considerable effort has gone toward developing standardized procedures for determining resilient modulus M r. In 1982, AASHTO recommended Protocol T to determine the resilient modulus of subgrade soil. Owing to a major shortcoming of T274-82, in which the use of higher stress levels could damage specimens in the preconditioning stage, the AASHTO Materials Committee withdrew T from the "Standard Tests" in In 1991, the test procedure was modified and replaced by an interim protocol AASHTO T ASSHO introduced designation T (i.e. SHRP Protocol P46) in 1992, which accommodated a sequence of applied stresses that takes into account the specific conditions representing states of stress underneath flexible and rigid pavements subjected to moving wheel loads. This procedure, partially based on T292-91, required a closed loop electro-hydraulic repeated loading system. A modified SHRP Protocol P46 was utilized in NCHRP Program Laboratory determination of Resilient Modulus for Flexible Pavement Design. However, serious flaws and high variability were found in the resilient modulus testing results of SHRP 1993/94 data. The data problems were caused by various factors, including inappropriate testing equipment (e.g., faulty electronics and mechanical problems), operator errors, inappropriate application of loads (e.g. non-symmetrical loading, and long duration of loading), as well as errors in deformation measurement. The shortcomings resulted in high variability of test data. To mitigate the problems, based on AASHTO T (and later on T294-94), a test procedure, LTPP Protocol P46, was developed together with Resilient Modulus of Unbound Materials Laboratory Startup and Quality Control Procedure (FHWA-RD ) for resilient modulus testing in support of the SHRP Long Term Pavement Performance (LTPP) Program. A modified version of this protocol has been adopted by AASHTO, designated as AASHTO T (2) and currently AASHTO T It should be noted that AASHTO abandoned the T294 SHRP Protocol P46, in As reported by Barksdale et al. (1997), the measured resilient moduli generally decreases with increasing number of conditioning stress repetitions, while the stress ratio used in stress conditioning has some effects on the permanent deformation of the material. Chen et al. (1995) found that the applied stress sequence has some effects on resilient modulus of granular materials. More specifically, the T294 testing procedure yielded higher values of moduli than those determined from the T292 testing procedure. 2.2 Major influencing factors Effect of stress level - Unbound pavement materials and subgrade soils are generally nonlinear and timedependent with properties depending on many factors, such as stress level, temperature, stress history, rate of loading, moisture content, etc. Among these, stress level is the most important influencing factor as reported by Lam (1982). Various types of relationships have been used to describe the dependency of M r on stress level, including the so-called "universal" constitutive equation (Uzan, 1985) M R K2 K3 θ σ d = K1pa pa pa that fits the LTPP M r test data fairly well. AASHTO 22 Design Guide recommends a modified version of the above equation k2 k3 θ τ oct MR = k1pa + 1 pa pa [1] [2] 237

3 where p a = atmospheric pressure, θ = bulk stress = σ + σ + σ = 3p with p being the mean normal stress, τ oct = octahedral shear stress, σ d = deviatoric stress, and k 1, k 2, k 3 (or K 1, K 2 and K 3) are regression constants with k 3 <. Generally, the resilient modulus increases with the bulk stress θ while it decreases with shear stress. In terms of stress duration and loading frequency, it has been found that haversine loading with duration of.1 sec and frequency of 2 to 3 applications per second, which is a representative of trucks moving at creep speed, yields test results that are not very sensitive to stress duration and the loading frequency. Effect of physical properties - The resilient modulus of a given material varies with the physical properties, including aggregate/soil type, gradation, Atterberg limits, density and moisture contents (or the degree of saturation). Previous studies at McMaster University show that crushed stone yields slightly higher values of M r than rounded stone and the M r increases with density, aggregate angularity and/or surface roughness. In terms of the total stress, the values of M r decrease if the material becomes saturated. On the other hand, when using effective stress, a unique relation between M r and the effective bulk stress θ is observed when the deviatoric stress varies in a relative small range. The influence of fines depends on gradation and angularity of aggregate. According to LPTT experimental data (Yau and Von Qu, 22), the liquid limit, plasticity index, and the amount of fines are important with respect to the resilient modulus of lower strength unbound aggregates, while the moisture content and density are important for higher strength materials. 2.3 Correlation between M r and CBR or other soil properties Owing to the complexity of laboratory resilient modulus testing and the potential inconsistency in M r estimates, when comparing values from various laboratories, the benefits gained by using more sophisticated testing can be undermined, which in turn has discouraged adopting laboratory resilient modulus testing in engineering practice. Direct resilient modulus testing is not the only way to estimate M r in engineering practice. An attractive procedure from a practical viewpoint is to estimate M r from, for example, the CBR taking into account the appropriate consideration of stress state in the material under the pavement subjected to moving loads (Lotfi et al., 1988). Simple relations for subgrade soils include: M r (MPa) =1.5 CBR (CBR<1) [3] or M r (MPa) = 17.6 CBR.64 [4] with the latter used for a Level 2 estimate following the AASHTO 22 Guide. Under some circumstances, the resilient modulus may be estimated based on AASHTO soil classification (Level 3 estimate). A potential benefit of estimating the M r from physical properties is that it may provide an approach to estimate seasonal variations in resilient modulus from seasonal changes in the materials' physical properties. This philosophy has been adopted in the development of the AASHTO 22 Design Guide under NCHRP Project 1-37A to predict changes in the physical properties of unbound pavement materials and soils and to estimate the effect those changes have on the resilient modulus. Care should however be exercised when estimating M r using correlations between M r and the physical properties of a soil due to the possibility of large errors in these correlations (George, 24). They should not be used to estimate the design resilient modulus for the design of high-volume roadways. 3. MATERIALS AND TESTING PROGRAMME 3.1 Materials and physical properties Representative aggregates were selected based on discussions with the Ministry. Immediately after receiving the material from MTO, each aggregate was spread out on the floor and air-dried. Thereafter, it was split up using a splitter box and bagged into quantities sufficient to fabricate samples and to perform various tests. Based on the sieve analyses and Ontario Provincial Standard Specifications OPSS 11 (MTO, 24), the 23 tested materials from various regions of MTO were classified as Granular A (11), Granular B (11) and Granular O (1). The grain size distributions for the five aggregates considered in this paper are shown in Figure 1. Percent Finer % 9% 8% 7% 6% 5% 4% 3% 2% 1% % 1 S15 Granular A S15 Granular B R4 Granular A R4 Granular B P9 Granular A 1 Diameter (mm) Figure 1. Grain size distributions of representative aggregates The aggregates can be described as follows: S15 Granular A - Well graded sand/gravelly sand with about 44.8% crushed, angular gravel particles; S15 Granular B - Well graded gravel/sandy gravel with 76.% subangular.1 238

4 to angular gray gravel; R4 Granular A - Well graded gravel/sandy gravel with 58.8% hard sub-angular to angular gravel particles; R4 Granular B-I - Poorly graded sand/gravelly sand with 45.5% rounded to sub-rounded gravels to cobbles; and P4 Granular A - Well graded gravel/sandy gravel with 51.4% hard sub-angular to angular gray gravel. Compaction tests were conducted according to Method C of AASHTO Designation T-99-1 (Standard Proctor) to determine the optimum moisture content w opt and the maximum dry density ρ dmax of each aggregate. Oversized particles (larger than 19. mm) were removed. Table 1, provided at the end of the paper, summarizes ρ dmax and the corrected optimum moisture contents taking into account oversized particles following ASTM D4718. As can be observed, the densities varied from 1993 to 2248 kg/m 3. Figure 2 presents two compaction curves, one (R4) follows the expected trend, and the other (S15) shows an uncharacteristic behaviour to moisture content. The experience that the authors wish to share here is that some Granular A materials (such as S15) have difficulty in retaining water, which flows to the bottom at higher water content. As a result, it was difficult to fabricate samples at w opt + 2%. 3.3 Sample preparation and test procedure All samples used for resilient modulus testing were compacted in a split mould using the vibration device shown in Figure 3, which meets the requirement of AASHTO T They were prepared and tested following the sample preparation method and the standard procedure described in AASHTO T According to the procedure, particles larger than 37.5 mm (i.e., 1/4 of the specimen diameter) were removed from aggregate samples prior to compaction. 215 Dry Density (kg/m 3 ) Water Content (%) Figure 2. Comparison of compaction curves. 3.2 Resilient modulus testing apparatus R4 Granular A S15 Granular A The resilient modulus loading device shown in Figure 3 was used for this study is a closed-loop, servo-controlled electro-hydraulic MTS testing machine with a function generator that is capable of applying repeated cycles of a haversine load pulse specified by AASHTO Designation T The triaxial cell that is capable of hosting the φ15 mm H3 mm specimen. In order to obtain an accurate measurement of the applied load and the resulting deformation of the test specimen, the capacity of the load cell and the limits of LVDTs are kn (2 lb) and 5 mm, respectively. It should be noted that the capacities of both the load cell and the LVDTs are slightly smaller than required by AASHTO Designation T This allowed a better accuracy of the measurements. Figure 3. Resilient modulus test components: 1 loading frame; 2 load cell; 3 LVDT; 4 triaxial cell; 5 split mould; 6 vibratory compaction device; and 7 test specimen Optimum moisture contents (w opt) obtained from standard Proctor test results were used as a guide to estimate appropriate moisture for compacting the M r test specimen. Owing to the fact that both the compaction method and the compaction effort for fabricating the M r test specimens were different from that corresponding to the Proctor tests, the actual optimum moisture content for an M r test specimen was lower, and thus specimens compacted at the Proctor optimum moisture content w opt appeared to be wet of optimum when compacting specimens by vibration. After a test specimen was fabricated, placed in the triaxial chamber, and instrumentation attached, the confining pressure was set to 13.4 kpa and 75 repetitions corresponding to a maximum deviatoric cyclic stress of 93.1 kpa was applied for sample conditioning. The purpose of sample conditioning is to eliminate the effect 239

5 of the interval between compaction and loading and to eliminate any initial loading versus reloading. Conditioning also aids in establishing better contact between the specimen and load platens, and in developing a more homogenous specimen. However, the conditioning procedure may cause unrecoverable deterioration of the specimen before actual Mr testing begins because of the high deviatoric stress levels and the large cyclic loading numbers, particularly for materials of low moduli. During the cyclical loading stage, the drainage valve remained open to minimize the build up of excess pore pressure. Following the conditioning, the resilient modulus test was carried out according to the loading sequences described in the AASHTO protocol. 4. RESILIENT MODULIUS TEST RESULTS Unbound pavement materials and subgrade soils tend to be nonlinear and time-dependent with the mechanical properties depending on many factors, such as stress level, temperature, stress history, rate of loading, moisture content, etc. Among these, stress level is the most important factor. In this study, the moisture sensitivity of M r is also investigated by performing tests at three moisture contents prepared at target values of w opt ± 2%. Furthermore, owing to the influence of compaction methods on w opt, when fabricating specimens for the resilient modulus tests, the w opt s were found to deviate from those determined by the Proctor. Although there were differences with respect to optimum water content, the dry densities did not appear to vary as much. 4.1 Sensitivity of resilient modulus to stress Figures 4 to 8 show the results for S15 Granular A and P9, respectively. One observes that the trends for the 4 of the aggregates are quite close, independent of Being Granular A or B. A close observations of the figures suggests that the pressure sensitivity of the resilient modulus can be approximated by the linear relation M = mp + b [5] R in which m and b are the slope and y-intercept, respectively, with the other terms taking on the usual meanings. Units used for M r and p in this paper are MPa and kpa, respectively. Table 1 summarizes the results from the data fitting exercise. One observes that the linear correlation for a particular water content and aggregate type is fairly good with R 2 values of.9 or higher. With regard to stress sensitivity, the following observations were made taking into account the results from the 23 aggregates: M r values increase with bulk stress θ (or pressure p) regardless of the applied confining pressure σ 3 and the deviatoric stress q. For a given confining pressure, M r tends to increase slightly with deviatoric stress, which may be partially attributed to the increase in bulk stress. For a given bulk stress, the deviatoric stress may cause an increase or a decrease of M r, depending on material properties. For aggregates with low CBR, high optimum moisture contents and higher percentage of particles finer than for example.85 mm, the resilient moduli tend to decrease with increasing deviatoric stresses. For most materials, the variation in M r due to q is not significant. In other words, the resilient modulus of most aggregates of this study is dominated by bulk stress w = 6.72 % w = 5.28 % w = 8.15 % Figure 4. Pressure sensitivity of M r for S15 Granular A w = 6.18% w = 5.15% w = 6.86% Figure 5. Pressure sensitivity of M r for S15 Granular B w = 3.27% w = 1.27% w = 5.1% Figure 6. Pressure sensitivity of M r for R4 Granular A. 24

6 w = 6.19% w = 4.11% w = 8.4% Figure 7. Pressure sensitivity of M r for R4 Granular B w = 6.56% w = 4.59% w = 2.6% Figure 8. Pressure sensitivity of M r for P9 Granular A. For the same category of materials such as Granular A, the M r values are scattered even when the specimens are compacted at the optimum moisture content. One concludes that the relation between M r and stress is sensitive to the aggregate source, as one might expect. 4.2 Sensitivity of resilient modulus to water content As mentioned previously, the resilient modulus samples were fabricated at thee different moisture contents within a targeted range of w opt ± 2%. The actual moisture contents of the 23 aggregates were found to vary as much as 4%. Nevertheless, the dry density was found to be not very sensitive to the water content in this range. The resilient modulus of the aggregates tended to decrease as the moisture content increased; however, this was not true for all aggregates. For some materials, the influence of moisture content on M r was considerably less than that for others, which is illustrated by comparing Figures 4 and 8. When analyzing the resilient modulus data from the 23 aggregates for moisture sensitivity, 8% of the samples were found to have a variation less than 2% relative to the mean M r for all aggregates for a particular bulk stress, with 5% of the samples having a variation less than 1%. One could conclude that small variations in moisture about the optimum during compaction will not have a profound influence on the resilient modulus. Nevertheless, additional research is warranted to understand the mechanism associated with the remarkable decrease of M r with the moisture for some aggregates. It should be noted that reductions in M r might be much larger if the moisture content variations are large. For example, Thom and Brown (1987) reported that increased moisture content may decrease the resilient modulus of a wet aggregate base material to approximately 1% of the value corresponding to the dry condition. Even though Eqs. [1] and [2] generally reproduce the M r data obtained from the 23 aggregates, a simpler equation can also be used to match experimental data reasonably. Figure 9 presents a linear regression of the test results from the 5 aggregates for specimens fabricated at optimum water content and drier than optimum. Also shown is the line (blue) corresponding to 1.5 standard deviations below the mean, with the mean being represented by the equation M = 1.73p [6] R which has R 2 =.84. One observes that a conservative estimate for resilient modulus of a material compacted at or below optimum can be obtained by shifting the line down, which for the shift shown corresponds to an intercept of 67 MPa. By, shifting the line down further to 5 MPa, one can capture most data points, including those specimens compacted at a nominal 2% above optimum. The authors are suggesting, given the uncertainty with regard to in-situ compaction, and that base/subbase materials are engineered soils consisting of quality aggregate in most cases, a conservative estimate for design M r can be obtained using Eq. (6), together with an appropriate downward shift Figure 9. Regression results for aggregates prepared at optimum/less than optimum water content. 241

7 4.3 Comparison of M r values from other studies Referring to Figure 1, the data points corresponding to the results for Granular A obtained for this study are contained in the hatched region, with the results from Lam s (1982) study identified by the broken lines and light shading and the LTPP findings (Von Quintus and Killingsworth, 1997; Yau and Von Qu, 22) identified by the shaded area surrounded by dashed lines below. This figure clearly shows that the moduli obtained in this study, which correspond to the AASHTO T37-99 specimen fabrication and testing protocol, are in the same range of LTPP resilient moduli data, but are considerably higher than those obtained in earlier studies performed by Lam. The lower values obtained in the Lam study may easily attributed to the procedures used in that particular study for fabricating specimens, which required freezing samples during the sample preparation stage, as well as size effects. Lam s samples were smaller having a diameter of mm. This comparison clearly demonstrates the need for standardization for sample preparation and testing. An increase in moisture content tends to decrease the resilient modulus. For most granular aggregates tested in this project, however, small variations (approximately ± 2%) in moisture about the optimum during compaction were found not have a profound influence on the resilient modulus. However, with an increase in fines content, moisture content may substantially reduce the resilient modulus. The resilient modulus varies with the physical properties such as particle shapes, gradation, and fines contents. The use of a linear regression between resilient modulus and pressure for design purposes that provides a reasonable lower bound would appear to be reasonable considering the uncertainties in resilient modulus testing and the variability in materials properties. This study has provided a starting point with respect to characterizing Ontario aggregates for road construction purposes. It is clear when comparing the results from this study to those obtained earlier, that additional research is required. Based on the findings of this study, it appears that Ontario is blessed with excellent aggregates, at least from a mechanical properties point of view. 6. ACKNOWLEDGEMENTS The following individuals deserve acknowledgement for their role in the study: Peter Koudys technician responsible for fabricating the equipment; Graeme Baker and Dave Heska for grain size and CBR testing and analysis. The authors would like to thank the Ministry of Transportation Ontario for providing financial and logistic support, in particular Becca Lane, as well as the individuals from the MTO regions that coordinated providing the aggregates. References Figure 1: Region of measured moduli for Granular A 5. FINDINGS AND OBSERVATIONS The following is a summary of the findings based on observations and the analysis of experimental results from the study completed for MTO: For most granular base/subbase materials, the bulk stress dominates the resilient modulus M r. In general, M r increases with an increase in the bulk stress. For aggregates with low CBR, high optimum moisture contents and higher percentage of particles finer than for example.85 mm, the resilient moduli tend to decrease with increasing deviatoric stresses. However, the variation of M r due to q is not significant. The resilient modulus of most aggregates of this study is dominated by bulk stress. The variation in M r, either an increase or a decrease, due to q is not significant. Barksdale, R.D., Alba, J., Khosla, N. P., Kim, R., Lambe, P. C. and Rahman, M. S., Laboratory Determination of Resilient Modulus for Flexible Pavement Design: Final Report. Chen, Dar-Hao, Zamman, M.M. and Laguros, J.G., Characterization of Base/Subbase Materials under Repetitive Loading. Journal of Testing and Evaluation, 23(3): George, P. K., 24. Resilient Modulus Prediction Employing Soil Index Properties. FHWA/MS-DOT-RD , p.64. Thom, N.H. and Brown, S.F., The effect of moisture on the structural performance of a crushed limestone road base. Transportation Research Record, 1121: Lam, Andrew Yong-Kung Ying-Man., Resilient moduli of flexible pavement materials. Thesis (M.Eng.), Department of Civil Engineering and Engineering Mechanics, McMaster University. Lotfi, H.A., Schwartz, C.W. and Witczak, M.W., Compaction specification for the control of subgrade 242

8 rutting. Transportation Research Record, 1196: MTO, 24. Material Specification for aggregates Base, subbase, selected subgrade, and backfill materials, OPSS 11. Uzan, J. (1985). Characterization of granular pavement materials. Transportation Research Record 122: Von Quintus, H. and Killingsworth, B., Design Pamphlet for the Determination of Layered Elastic Moduli for Flexible Pavement Design in Support of the 1993 AASHTO Guide for the Design of Pavement Structures. FHWA-RD Yau, A. and Von Qu, H. L., 22. Study of LTPP Laboratory Resilient Modulus Test Data and Response Characteristics: Final report. Federal Highway Administration, Publication No. FHWA-RD Sample Table 1: Summary of resilient modulus tests: moisture content and density w opt ρ max ρ achievd w achieved m b R 2 (%) (kg/m 3 ) (kg/m 3 ) (%) (MPa) S15 Granular A S15 Granular B R4 Granular A R4 Granular B P9 Granular A