Optimizing Pay Factors
The ideal goal of a paving project is to place a pavement with a gradation that won’t rut, contains 4-5% asphalt above that absorbed, have a film thickness of 7-10 microns on the aggregate, is compacted well with no more than 8% voids and is not damaged by water. In addition, the asphalt must be able to stress relax well enough when it is cold so the pavement doesn’t crack. Although many won’t agree, it really doesn’t matter whether Marshall, Hveem or Superpave mix design is used since all the mix design really does is to determine how much asphalt should be used (although with coarse mixes a 6” Marshall is advised).
Finally the contractor wants full pay.
It needs to be reemphasized that if the pavement is susceptible to damage by water, the life of the pavement will be greatly diminished. It is my opinion that the most severe stripping test should be used, and it might be well to run the test in a salt brine as well as in water. And the test should be run on samples with 6-8% voids, never at the mix design void content. The question of how long the protection of a particular antistrip lasts should be considered also, however that is for another day.
When statistical specifications are being used, there are two basic factors that are necessary to get full pay; accuracy and precision. The pay factor is determined from a ratio consisting of a value that measures how accurately the test data represents the job mix formula divided by a value that measures how precise the data are, i.e., how big the spread of data, usually in a lot of four tests.
First, accuracy. The first parameter measured is the distance within the specification limits of the mean of the test data from the control limits. To achieve accuracy, several factors must come into play. These are some examples:
The aggregate gradations must be accurately know and uniform. That means that sampling must be done properly, and it is not easy to get an accurate sample. The gradation of the job mix formula must accurately reflect the material that is going into the pavement.
Any bias in the determination of the % asphalt must be known exactly, i.e. the correction factor for the furnace must be accurately determined, and that determination should be for the furnace being used.
Nuclear gages used for compaction must be calibrated, and it would be well if they were calibrated against cores.
To get the best resistance to rutting, a coarse gradation should be used, however mixes with coarse gradations have a tendency to segregate. Which brings us to the second important factor in calculating the pay factor; precision.
Precision measures how close replicate tests are to each other. Hot mix tends to segregate in a silo and as it comes out behind the paving machine. The mix will tend to be finer behind the tunnels and coarse at the edges and between the tunnels. Thus improper sampling can cause a loss of precision. If sampling is suspected to be a cause of variability, a plot of the #4 data vs. % asphalt can be helpful. If the % asphalt increases with increased % passing the #4, segregation is the cause, not variability of the gradation of the aggregate feed.
Contractors who get 105% pay factors pay close attention to both how close their mixes are to the job mix formula and how uniform the mix is. Note. There is a calculable penalty built into specifications for which the maximum pay factor is only 100%.
For more information on how specifications work, to get help in maximizing pay factors, or on seminars on various aspects of asphalt technology contact Robert L. Dunning, email@example.com at Petroleum Sciences, Inc., www.petroleumsciences.com.
stripping, accuracy and precision, rutting, statistical specifications