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OCR for page 152
152 A Manual for Design of Hot Mix Asphalt with Commentary
should understand the principles involved. The information in this chapter, therefore, focuses
on these principles--not the mathematical details. Readers interested in the technical details
underlying the information in this chapter should refer to the Commentary on the HMA Mix
Design Manual. Frequent reference is also made to how the HMA Tools spreadsheet is used in
the mix design process; the examples have been constructed around HMA Tools.
In compiling this chapter, it is assumed that the reader has reviewed Chapter 8 on dense-graded
HMA mix designs and understands both the concepts involved in the mix design process and
the use of most of the functions in the HMA Tools spreadsheet. Readers unfamiliar with either
of these topics should take the time to review Chapter 8.
RAP Sampling
Samples of RAP can be obtained from several locations, including the roadway by coring,
trucks hauling milled material for stockpiling, stockpiles prior to processing, and stockpiles after
processing. Milling and processing operations break down some of the aggregate in the RAP,
producing finer gradations with increased percentages passing the 0.075-mm (#200) sieve. Since
a representative sample of RAP will be used directly in the mixture design process, it is critical
that RAP samples obtained for HMA mixture design be representative of the RAP that will be used
in the mixture. For this reason, the location recommended for sampling RAP is from stockpiles
of the RAP after final processing.
Sampling RAP from a stockpile is similar to sampling aggregate from a stockpile, except crusts
form on RAP stockpiles that must be removed before samples can be taken. General guidance
for stockpile sampling is provided in AASHTO T 2. As discussed in AASHTO T 2, segregation is
a major concern when sampling from stockpiles. The preferred approach for stockpile sampling
is to use a loader or other power equipment to obtain smaller sampling piles from selected
locations within the main stockpile. The RAP sample for each location is then taken from the
smaller sampling pile.
RAP stockpiles should be sampled from at least five locations distributed throughout the pile.
A larger number of samples--up to 20 or more--is desirable, since this will allow a more
accurate characterization of the RAP and permit the highest possible RAP content in the final
mix design(s). The sample size depends on the number of mixture designs that will be developed
using the RAP in the stockpile. At each sampling location, obtain 10 kg (22 lb) of RAP for each
mixture design that will be prepared, plus 5 kg (11 lb) for characterization of the RAP. For example,
if three mixtures (a base, intermediate, and surface) will be designed using the same RAP, then
obtain 35 kg (77 lb) of RAP at each sampling location. This sample size will provide sufficient
material to characterize the properties and variability of the RAP stockpile and provide a rep-
resentative sample for use in mixture design.
There are two objectives for the RAP sampling. The first is to determine the average and vari-
ability (in terms of standard deviation) of the binder content and aggregate gradation in the RAP
in the stockpile. For this analysis, a 5 kg (11 lb) sub-sample should be split from the sample taken
at each stockpile location using the methods described in AASHTO T 248. This sub-sample will
then be tested to determine the average and standard deviation of the binder content and aggre-
gate gradation within the RAP stockpile. As discussed in the next section, variability is an impor-
tant consideration in the selection of feasible RAP contents that can be considered in design. The
second objective of the sampling is to obtain representative materials for the mixture design. A
representative sample is formed by combining the remaining portion of the samples from each
sampling location. From this representative RAP sample, aggregate properties and, if required,
binder properties will be determined and specimens for volumetric and performance analysis
