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CHAPTER 9
Reclaimed Asphalt Pavement
Chapter 9 of the Manual deals with incorporation of reclaimed asphalt pavement (RAP) into
HMA mix designs. This is a complicated topic potentially involving numerous calculations:
1. Calculation of the blended aggregate gradation, including contribution from the RAP.
2. Calculation of the binder content, again including contribution from the RAP.
3. Calculation of the blended binder grade, based upon both the new binder added and the
binder contributed from the RAP.
4. Calculation of the required new binder grade needed to achieve a specified binder grade, given
a certain RAP content and a binder grade for the RAP binder.
5. Calculation of the minimum and maximum RAP that can be used in a mix, given a new
binder grade and a grade for the RAP binder.
6. Estimation of the variability in aggregate gradation and binder content, given a job mix formula
(JMF) containing a certain amount of RAP.
7. Estimation of the maximum amount of RAP that can be used in a mix without exceeding typ
ical limits on variability of production, given variability in the RAP stockpiles being used.
The mathematics of some of these calculationsin particular the variability calculations
can be challenging. For this reason, HMA Tools has been designed to perform these calculations,
and the Manual in general simply discusses how to use this spreadsheet to perform the needed
calculations during the mix design process. This avoids having to show and document some
involved equations. The Commentary for Chapter 9 therefore involves showing and describing
the equations used in HMA Tools to perform these RAP calculations, along with any associated
assumptions and/or simplifications.
Chapter 9 is structured for the most part as a series of example problems of increasing com
plexity. The section below, on critical tables, figures, and equations therefore is mostly organized
on the basis of these examples, presenting and describing the critical information used in solving
each example problem. Calculations involving RAP binder properties are based on Appendix A
of AASHTO M 323 and are not documented in detail here.
Much of what is contained in Chapter 9 of the Manual has been based on NCHRP Report 452
(46). This is an excellent reference for technicians and laboratory engineers responsible for the
design and/or analysis of HMA mix designs containing RAP.
Example 1. Gradation and Binder Content Analysis for
an HMA Mixture Containing RAP
The computation of blends for mixtures incorporating RAP is a little different than that for
mixtures made with all new stockpiles. When RAP is used, the RAP material that is added includes
both the RAP aggregate and the RAP binder. Since gradation data are based on the weight of
253
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254 A Manual for Design of Hot Mix Asphalt with Commentary
aggregate, and binder contents are based on the total weight, the stockpile percentages must be
adjusted for combined gradation analysis based on the amount of binder contained in the RAP.
The binder included in the RAP is computed from Equation 8:
PbRAPi
wbRAPi = psRAPi × (8)
100
where
wbRAPi = weight of RAP binder from RAP stockpile i, wt%
psRAPi = percentage of RAP stockpile i in the total blend,%
PbRAPi = binder content of RAP stockpile i, wt%
The total weight of binder contributed by all RAP stockpiles is the sum of the weight con
tributed by each RAP stockpile and is computed from Equation 9:
j
wbRAPTotal = wbRAPi (9)
i =1
where
wbRAPTotal = total weight of RAP binder from all RAP stockpiles, weight%
wbRAPi = weight of RAP binder from RAP stockpile i, wt%
j = total number of RAP stockpiles
The total binder content for the mix is simply calculated by adding the weight of binder con
tributed by all RAP stockpiles to the weight of new binder added.
For gradation analysis, the percentage of each stockpile based on the total weight of aggregate
is needed. The percentage of each new aggregate stockpile based on the total weight of aggregate
is given by Equation 10:
psnewk
pnewk = × 100% (10)
(100  wbRAPTotal )
where
Pnewk = percentage of new aggregate k, weight% of total aggregate
psnewk = percentage of new aggregate stockpile k in the total blend, weight%
wbRAPTotal = total weight of RAP binder from all RAP stockpiles, weight%
The percentage of each RAP aggregate based on the total weight of aggregate is given by
Equation 11:
psRAPi  wbRAPi
pRAPi = × 10
00% (11)
(100  wbRAPTotal )
where
pRAPi = percentage of RAP aggregate i, weight% of total aggregate
psRAPi = percentage of RAP stockpile i in the total blend, weight%
wbRAPi = weight of RAP binder from RAP stockpile i, weight%
wbRAPTotal = total weight of RAP binder from all RAP stockpiles, weight%
For each sieve, the gradation of the blend of the stockpiles is then computed using the per
centage of each stockpile based on the total weight of aggregate using Equation 12:
n
pnewk j pRAPi
tpp = × ppk + × ppi (12)
k =1 100 i =1 100
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Commentary to the Mix Design Manual for Hot Mix Asphalt 255
where
tpp = total percent passing a given sieve, weight% of total aggregate
Pnewk = percentage of new aggregate k, weight% of total aggregate
pRAPi = percentage of RAP aggregate i, weight% of total aggregate
ppk = percent passing a given sieve for new aggregate k, weight%
ppi = percent passing a given sieve for RAP aggregate i, weight%
j = number of RAP stockpiles
n = number of new stockpiles
Example 2. Calculation of Mean, Standard Deviation,
and Maximum Allowable RAP Content for a Single
RAP Stockpile
The mean is calculated using Equation 13 (47):
n
Xi
X = (13)
i =1 n
where
_
X = stockpile average
Xi = result for location i
n = total number of locations tested
The standard deviation is calculated using Equation 14 (47):
n
( Xi  X )
2
i =1
s= (14)
n 1
where
_s = standard deviation
X = stockpile average
Xi = result for location i
n = total number of locations tested
Derivation of the procedure for calculation of the maximum allowable RAP content is as fol
lows. ASTM D 4460 gives equations for calculating standard deviation values for quantities deter
mined from calculations involving two other values. From these equations, the following formula
for calculating the standard deviation of a blend of two materials can be derived:
m = 2a ( ) b ( a b) a 2
2 + 1 2 + X 2 + X 2 2 (15)
where
m = standard deviation of the mixture
a = standard deviation of component "a"
b = standard deviation of component "b"
= proportion of component "a" in the mixture
_
_a = mean value for component "a"
X
Xb = mean value for component "b"
= standard deviation of the proportions
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256 A Manual for Design of Hot Mix Asphalt with Commentary
We can rewrite this for percent passing for a selected sieve for HMA mixtures consisting of a
blend of new HMA materials with RAP:
PM = w R PR + w N PN + ( PR + PN ) w
2
2 2 2 2 2 2 (16)
where
PM = standard deviation of percent passing for a selected sieve for the mixture with RAP
wR = weight fraction of RAP in the mixture
PR = standard deviation of percent passing for the selected sieve for the RAP
wN = weight fraction of new materials (new HMA) in the mixture
= (1  wR)
_PN = standard deviation of percent passing for the selected sieve for the new HMA
_ R = mean value for RAP% passing for the selected sieve
P
PN = mean value for new HMA% passing for the selected sieve
w = standard deviation of the weight fractions, also called "batching variability,"
Equation 17 can be solved for the maximum amount of RAP that can be added to new material
without increasing the standard deviation for percent passing on the selected sieve above a selected
maximum value by application of the quadratic equation
b + b 2  4ac
Max . RAP % = × 100% (17)
2a
where
Max. RAP% = maximum amount of RAP that can be added to the mix, weight%
a = 2 PR + PN
2
b =  2 2 PN_ _
c = 2 PN + (P PN + P N) w  PM/Max
2 2 2 2
and PM/Max is the maximum allowable standard deviation for percent passing
for the selected sieve.
Equations 1 and 2 can be rewritten for asphalt content rather than for aggregate percent pass
ing, calculated using the following equation:
BM = w R BR + w N BN + ( BR + BN ) w
2
2 2 2 2 2 2 (18)
where
BM = standard deviation of binder content (weight%) for the mixture with RAP
wR = weight fraction of RAP in the mixture
BR = standard deviation of binder content (weight%) for the RAP
wN = weight fraction of new materials (new HMA) in the mixture
= (1  wR)
_
BN = standard deviation of binder content (weight%) for the new HMA
_ R = mean value for the RAP binder content, weight%
B
BN = mean value for new HMA binder content, weight%
w = standard deviation of the weight fractions or "batching variability"
As for Equation 1, Equation 3 can also be solved for the maximum amount of RAP that can
be added to new material without increasing the variability above a selected maximum by appli
cation of the quadratic equation:
b + b 2  4ac
Max . RAP % = × 100% (19)
2a
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Commentary to the Mix Design Manual for Hot Mix Asphalt 257
where
Max. RAP% = maximum amount of RAP that can be added to a mix without increasing the
production variability, weight%
a = 2 BR + BN
2
b = 2BN _ _
2
c = 2 BN + (B R + B N)w  BM/Max
2 2 2 2
and BM/Max is the maximum allowable standard deviation for binder content
for the entire mix, including RAP.
The approach used in the Manual in applying Equations 17 and 19 to calculate the maximum
allowable RAP in an HMA mix design is to assume that the maximum allowable standard devia
tion for the final HMA should be no larger than the standard deviation for the new materials in the
mix. This is equivalent to saying that the amount of RAP should be limited so that the overall
variability in HMA production is not increased above what it would normally be without the
addition of any RAP. This approach simplifies some of the calculations, and as discussed below,
if typical variability in aggregate% passing and binder contents are assumed, the mix designer
can determine the maximum allowable RAP without knowing the existing HMA variability or
the maximum allowable variability desired by the producer. The maximum amount of RAP that
can be added to a mix simply becomes a function of the RAP variability.
A critical issue in this approach is what values to use for typical standard deviations for HMA
production when applying Equations 17 and 19. The simplest and most conservative approach
is to base the standard deviation values on information given in ASTM D 3515: Standard Speci
fication for HotMixed, HotLaid Bituminous Paving Mixtures. Although this document does not
specify standard deviations for aggregates and asphalt binder, it does give tolerances; these are
shown in Table 22. The question becomes what is the ratio between these tolerances and typical
standard deviations? The standard deviation values corresponding to those given in ASTM D 3515
must be much smaller than the tolerances, otherwise, plants would often violate these specified
tolerances. For example, if typical standard deviation values were onefourth the specified toler
ance, HMA plants would exceed these limits one time in 20. This is probably too frequent; a
somewhat smaller standard deviation is more likelyonefifth of the specified tolerance range
appears to provide reasonable estimates of typical standard deviation values in wellrun HMA
plants (typical variability of HMA production is discussed in more detail in Chapter 12 of the
Manual and the Commentary). The resulting estimated typical standard deviations are also
shown in Table 22.
A second complication arises from the uncertainty in estimating standard deviations. When sev
eral samples of RAP are taken and used to estimate the standard deviation, the resulting value is an
estimate. In fact, unless the number of replicate samples is about 30 or higher, the uncertainty
Table 22. Production Tolerances
for Hot Mix Plants as Given in
ASTM D 3515.
Typical
Standard
Sieve Size Tolerance Deviation
> 12. 5 mm ± 8.0% 3.2%
4.75 and 9.5 mm ± 7.0% 2.8%
1.18 and 2.36 mm ± 6.0% 2.4%
0.300 and 0.600 mm ± 5.0% 2.0%
0.150 mm ± 4.0% 1.6%
0.075 mm ± 3.0% 1.2%
Asphalt binder ± 0.5% 0.2%
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258 A Manual for Design of Hot Mix Asphalt with Commentary
in the estimate can be quite large. To be conservative and to make certain that the variability in
plant production will not be increased to an unacceptable level by the addition of RAP, an upper
confidence limit for the standard deviation should be used, rather than the actual calculated
value. This upper confidence limit is calculated using the following equation (47):
(n  1) s 2
U= (20)
2 ( ; n  1)
where
U = upper confidence limit for the standard deviation at 1 confidence level; use in place of
PR and/or BR in Equations 2 and 4.
n = number of measurements used in estimating the standard deviation s
2 = chisquared distribution with confidence level 1 and n1 degrees of freedom
A value for of 0.20 (an 80% confidence level) appears to provide reasonable values for U and
the resulting calculated maximum allowable RAP contents. One advantage to using an upper
confidence limit U for the standard deviation, rather than the actual estimate, is the effect of sam
ple size on the resulting value of Uthe larger the number of RAP samples used to estimate the
standard deviation, the lower will be the value of U and the greater the resulting maximum allow
able RAP content. Producers who take large numbers of RAP samples to characterize their stock
pile will be rewarded, while those using only a few samples will be severely limited in how much
RAP they can use in their mixtures. For example, for the case where PN = PM/max = 2.0, and
PR is estimated to be 4.0, if the RAP standard deviation is based on n = 5 samples, the maximum
allowable RAP content is 17%. However, if the RAP standard deviation is based on n = 10 sam
ples, the maximum allowable RAP content increases to 27%.
A third important question in applying the equations for analyzing the effect of RAP on HMA
production variability is what is a typical value for the standard deviation of the proportions, also
called "batching variability." Information is given in ASTM D 995: Standard Specification for
Mixing Plants for HotMixed, HotLaid Bituminous Paving Mixtures on the required accuracy of
aggregate scales, control of automated plants, and related information that can be used to estab
lish typical blending standard deviations for HMA plants:
· The accuracy of metering of asphalt binder must be within 1.0% when compared to another
metering device or to within 0.5% when compared to test weights. Assuming a ±2 s precision
applies to the comparison with test weights, this implies a blending standard deviation for
asphalt binders of 0.25% or 0.0025.
· Aggregate scales for batch plants must also be accurate to within 0.5% when compared to test
weights, again, implying a blending standard deviation of 0.25% or 0.0025.
· Automatic proportioning systems, for both batch plants and drum plants, must batch aggre
gate (other than mineral filler) to within ±1.5% of the total batch weight, or for continuous
drum plants, to within ±1.5% of the mix production per drum rotation/unit time. Assuming
that this tolerance refers to comparison with test weights or similarly accurate reference, and
that a ±2 s precision is implied, this translates to a blending standard deviation of 0.75%
or 0.0075. The required tolerance for mineral filler is ±0.5%, implying a blending standard
deviation of 0.0025. For asphalt binder, the required tolerance is ±0.1%, implying a blending
standard deviation of 0.0005.
Assuming that the tolerance for adding RAP to a mix is similar to that for aggregate, and con
servatively applying the standard deviation calculated from the required tolerance for automated
plants, the blending standard deviation for analyzing RAP variability should be 0.0075. It should
be noted that this is based on the maximum permitted tolerance in automated plants and is thus
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Commentary to the Mix Design Manual for Hot Mix Asphalt 259
Standard Deviation for RAP Aggregate % Passing, %
0 1 2 3 4 5 6 7 8
50
Max. RAP Content, Wt. %
40
30
20
10
Sieve size, mm: 0.075 0.150 0.300 1.18 4.75 > 9.5
to 0.600 to 2.36 to 9.5
Figure 7. Maximum RAP content as a function of RAP aggregate
sieve size and standard deviation (Figure 93 in the Mix Design
Manual).
a conservative assumption. The actual blending variability in many plants will probably be lower
than this.
HMA Tools calculates mean, standard deviation, the upper confidence limit for standard devi
ation, and the maximum allowable RAP content based on variability for up to four different RAP
stockpiles. This analysis uses Equations 13 through 20 along with the assumptions described con
cerning typical variability in HMA production and batching variability.
Example 3. Determination of Maximum Allowable RAP
Content Based on Variability Analysis Using
the Graphical Approach
This example problem is essentially identical to the previous one, but in this case a simplified
graphical approach is used in determining the maximum allowable RAP. This approach involves
the use of four chartsFigures 93 through 96 in the Manualto determine the maximum allow
able RAP content. These charts are reproduced here for the convenience of the reader. The charts
have been developed based on the analysis described above, with a sample size of N = 5; the sam
ple size is small because it has been assumed that those producers wishing to use this simplified
approach would probably not want to use large sample sizes of RAP. Figures 7 and 8 (93 and
50
Max. RAP Content, Wt. %
45
40
35
30
25
20
15
0.2 0.3 0.4 0.5 0.6 0.7
Binder Standard Deviation
Figure 8. Maximum RAP content as a function of standard
deviation for asphalt binder content (Figure 94 in the Mix Design
Manual). For n = 5 Samples from a single RAP stockpile.
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260 A Manual for Design of Hot Mix Asphalt with Commentary
94 in the Manual) are for the case where only a single RAP stockpile is used in a mix design. The
development of these charts was straightforward, involving a direct application of the equations
given above. As an example of using these charts, if a given RAP stockpile has a standard devia
tion of 4.0% for aggregate passing the 0.60 mm sieve, the maximum allowable RAP content can
be found from Figure 7 to be 30%. It must be emphasized that Figure 7 is based on standard devi
ations calculated using at least 5 samplesit should not be applied to standard deviations calcu
lated using a lower number of samples. It can be used for standard deviations calculated using
larger samples, but the results will be overly conservative. Also, in developing these figures it is
assumed that the difference in percent passing between the RAP aggregate and the new aggre
gate will not exceed these limits: 30% for mineral filler; 40% for passing the 0.150 mm sieve, and
50% for all other aggregate sizes. If the differences exceed these limits, the difference term in
Equations 15 through 18 starts to become significant and must be considered in the calculation.
In using Figure 7 in an actual mix design, all aggregate sizes would be evaluated, and the overall
maximum allowable RAP content would be the lowest value calculated for all sieve sizes. The
maximum RAP content based on asphalt binder standard deviation should also be evaluated
(Figure 8, or Figure 94 in the Manual)again, the lowest calculated of these maximum RAP
contents should be applied.
Figures 7 and 8 will in general not be accurate when more than one RAP stockpile is used in a
mix design. This is because as RAP stockpiles are blended, the variability of the resulting stockpile
will be reduced. The more stockpiles in a blend, the lower will be its variability when compared to
the average variability for the materials in the blend. The standard deviation for % passing and
binder content for a blend of three or more RAP stockpiles can be accurately estimated by sequen
tial application of Equations 15 and 17, respectively. This calculation is done as follows. The stan
dard deviation for % passing for a blend of Stockpiles 1 and 2 is first calculated. Then, the standard
deviation is calculated for a second blend, made up of stockpile 3 and the blend of Stockpiles 1
and 2. If a fourth stockpile is used, the standard deviation for a blend of Stockpile 4 and the
blend of Stockpiles 1, 2, and 3 is calculated. This is done for both aggregate % passing and
binder content. This approach is very accurate and is used in HMA Tools in calculating the
standard deviation values for RAP blends involving more than two stockpiles. Unfortunately,
constructing graphs similar to Figures 7 and 8 for this situation is somewhat complicated.
The approached used for the Manual was to develop an empirical relationship between the
average standard deviation of a blend of stockpiles and the standard deviation calculated
using Equations 15 and 17. The data was generated using a Monte Carlo approach. A total of
500 data points were generated, with simulated RAP stockpile blends composed of from two
to four separate stockpiles, having a wide range of standard deviations along with a wide
range of blend compositions. The relationships between average standard deviation and cal
culated standard deviation for % passing is shown in Figure 9, and for binder content in Fig
ure 10. These plots include the regression function for predicted standard deviation, along
with the 80% upper prediction limit. In order to provide a conservative estimate of standard
deviation, the upper prediction limits were used in generating the charts for determining
maximum RAP content in HMA designs using more than one stockpile. The equation for
estimating the 80% upper prediction limit for standard deviation of a blend of RAP stock
piles for aggregate% passing is as follows:

SD ( PP , 80% UPL ) = 0.70 × SD1.023 (21)
where
SD(PP, 80% UPL) = Estimated standard deviation for % passing for the overall RAP stockpile
blend, 80% upper prediction limit

SD = average standard deviation for % passing for the RAP stockpile blend
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Commentary to the Mix Design Manual for Hot Mix Asphalt 261
10.0
Overall RAP Std. Dev.
1.0
Data
Predicted Std. Dev.
80 % Upper Prediction Limit
0.1
1.0 10.0
Average RAP Standard Deviation for % Passing
Figure 9. Relationship between average RAP
standard deviation for % passing and calculated
overall RAP standard deviation for % passing.
The 80% upper prediction limit for standard deviation of the binder content for a blend of
RAP stockpiles can be estimated using the following equation:
SD ( BC , 80% UPL ) = 0.69 × SD 0.973 (22)
where
SD(BC, 80% UPL) = Estimated standard deviation for binder content (weight%) for the over
all RAP stockpile blend, 80% upper prediction limit

SD = average standard deviation for binder content (weight %) for the RAP
stockpile blend
Using Equations 21 and 22, Figures 11 and 12 were developed, respectively, showing maxi
mum allowable RAP content as a function of average RAP standard deviation values. It should
be noted that these charts are conservative and like Figures 7 and 8 are based on standard devi
ation values calculated using N = 5 independent samples of RAP. HMA Tools uses the pertinent
equations directly, without any assumptions or simplifications. HMA Tools will therefore pro
vide more accurate estimates of maximum allowable RAP contents. Furthermore, in general, the
estimated maximum RAP contents found using HMA Tools will be somewhat larger than those
found with the charts. This is especially true when more than five samples of RAP are used in esti
mating standard deviation values, when more than one RAP is used in a mix design, or both.
1.0
Overall RAP Std. Dev.
0.1
Data
Predicted Std. Dev.
80 % Upper Prediction Limit
0.0
0.1 1.0
Average RAP Standard Deviation for Binder Content
Figure 10. Relationship between average RAP
standard deviation for binder content and calculated
overall RAP standard deviation for binder content.
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262 A Manual for Design of Hot Mix Asphalt with Commentary
Average Standard Deviation for RAP Aggregate % Passing
0 1 2 3 4 5 6 7 8 9 10
50
Max. RAP Content, Wt. %
45
40
35
30
25
20
15
Sieve size, mm: 0.075 0.150 0.300 1.18 4.75 > 9.5
& 0.600 & 2.36 & 9.5
Figure 11. Maximum RAP content as a function of average standard
deviation for aggregate % passing (Figure 95 in the Mix Design Manual).
For n = 5 Samples from a blend of RAP stockpiles, and no stockpile
making up more than 70% of the RAP blend.
Calculation of Aggregate Specific Gravity Values
for RAP Stockpiles.
The bulk specific gravity of each aggregate stockpile used in an HMA mixture is needed for the
computation of the voids in the mineral aggregate (VMA). Two methods can be used to deter
mine the bulk specific gravity of the RAP aggregate (46). The first is to estimate the bulk specific
gravity of the RAP aggregate from the RAP binder content, the maximum specific gravity of the
RAP, and estimates of the binder absorption in the RAP and the specific gravity of the RAP
binder. The second is to measure the bulk specific gravity of the coarse and fine fraction of the
RAP aggregate after removing the binder with the ignition oven or solvent extraction. Details of
these approaches are discussed below (46).
Estimating RAP Aggregate Bulk Specific Gravity
In this approach, the maximum specific gravity of the RAP is measured in accordance with
AASHTO T 209. The maximum specific gravity is measured on a sample split from the repre
sentative sample formed for the RAP aggregate and binder analysis. The measured maximum
specific gravity, the average RAP binder content from the variability analysis, and an estimate of
the RAP binder specific gravity are then used to calculate the effective specific gravity of the RAP
aggregate using Equation 23 (Equation 91 in the Manual) (46):
50
Max. RAP Content, Wt. %
45
40
35
30
25
20
15
0.2 0.3 0.4 0.5 0.6 0.7
Average Binder Standard Deviation
Figure 12. Maximum RAP content as a function of average standard
deviation for asphalt binder content (Figure 96 in the Mix Design
Manual). For n = 5 Samples from a blend of RAP stockpiles, and no
stockpile making up more than 70% of the RAP blend.
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Commentary to the Mix Design Manual for Hot Mix Asphalt 263
(100  Pb )
Gse = (23)
100 Pb

Gmm Gb
where
Gse = effective specific gravity of the RAP aggregate
Gmm = maximum specific gravity of the RAP measured by AASHTO T 209
Pb = RAP binder content, wt %
Gb = estimated specific gravity of the RAP binder
The bulk specific gravity of the RAP aggregate can then be estimated from Equation 24 (Equa
tion 92 in the Manual), which is a rearranged version of the equation used in volumetric analy
sis to compute asphalt absorption.
Gse
Gsb = (24)
ba se
P G
+1
100 × Gb
where
Gsb = estimated bulk specific gravity of the RAP aggregate
Gse = effective specific gravity of the RAP aggregate from Equation 23
Pba = estimated binder absorption for the RAP, wt% of aggregate
Gb = estimated specific gravity of the RAP binder
The overall error associated with this analysis is difficult to quantify. It depends on the preci
sion of the maximum specific gravity measurement, the accuracy of the RAP binder content
measurement, and the estimated RAP binder absorption and specific gravity. As shown in the
analysis below, the accuracy of the RAP binder content in turn depends on the accuracy of the
correction factor that was used to analyze the ignition oven data.
The singleoperator precision of the maximum specific gravity test, AASHTO T 209, is 0.011
when the dryback procedure is not required and 0.018 when it is. These are somewhat better
than the singleoperator precision of the aggregate bulk specific gravity tests which are 0.032 for
fine aggregate (AASHTO T 84) and 0.025 for coarse aggregate (AASHTO T 85). The potential
error associated with estimating the bulk specific gravity of the RAP binder is small. For a typi
cal mixture it is only ±0.002 for a ±0.010 error in the bulk specific gravity of the binder. Poten
tial errors associated with errors in the RAP binder content or the RAP binder absorption are
significantly larger. These errors are shown in Figure 13 for RAP having a maximum specific
gravity of 2.500, a total binder content of 4.0%, and binder absorption of 0.5%. In this case
underestimating the absorbed binder by 0.3% results in an overestimation of the bulk specific
gravity of the RAP aggregate of 0.020. Underestimating the total binder content of the RAP by
0.5% results in an underestimation of the bulk specific gravity of the RAP aggregate of 0.021.
Thus the accuracy of estimating the RAP aggregate specific gravity from the maximum spe
cific gravity and binder content of the RAP depends mostly on the accuracy of the estimated cor
rection factor used to determine binder content with the ignition oven and the accuracy of the
assumed binder absorption. The correction factor for the ignition oven should not be in error
by more than 0.3% and the assumed binder content should not be in error by more than 0.2%
to obtain estimated RAP aggregate specific gravity values with similar accuracy as those mea
sured in AASHTO T 84 and T 85. As discussed earlier, correction factors for the ignition oven can
be established by performing both the ignition oven and solvent extraction analyses on split sam
ples from at least three locations in the RAP stockpile.
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264 A Manual for Design of Hot Mix Asphalt with Commentary
0.040
RAP Binder Content
RAP Binder Absorption
ERROR IN BULK SPECIFIC GRAVITY OF RAP
0.030
0.020
0.010
AGGREGATE
0.000
0.010
0.020
0.030
0.040
0.6 0.4 0.2 0 0.2 0.4 0.6
ERROR IN RAP BINDER CONTENT OR ABSORPTION, %
Figure 13. Potential errors in bulk specific gravity of the RAP aggregate
for errors in RAP binder content and binder absorption (Figure 97 in the
Mix Design Manual).
Measuring RAP Aggregate Specific Gravity
If a reasonable estimate of the binder absorption for the RAP is not available, the specific grav
ity of the RAP aggregate can be measured after removing the RAP binder using an ignition oven
or solvent extraction. The specific gravities of the coarse and fine fractions of the RAP aggregate
are measured in accordance with AASHTO T 85 and AASHTO T 84, respectively.
HMA Tools and RAP Aggregate Specific Gravity
HMA Tools has been designed so that either approach can be used to estimate RAP aggregate
specific gravity values. If the specific gravity values are to be estimated from maximum theoret
ical specific gravity, binder content, and related information, the data is entered in cells C6:F9 in
worksheet "RAP_Aggregates." If actual measured values for RAP aggregate specific gravity are
used, these are entered in cells C11:F14. The calculated values for bulk and apparent specific grav
ity for each of up to four RAP stockpiles then appear in cells C16:F17. If data for both methods
are entered in the worksheet, HMA Tools will use the measured aggregate specific gravity values
in estimating the RAP specific gravity values. The estimated water absorption for each RAP
stockpile appears in cells C18:F18.
RAP Binder Properties
The section in the Manual on RAP binder properties is based on information and equations
given in Appendix A of AASHTO M 323. The various equations and calculations described herein
have been implemented in HMA Tools. Using HMA Tools to perform calculations related to RAP
binder properties should give results identical to manual calculations carried out following the
instructions given in Appendix A of AASHTO M 323.