Volume 30, Issue 3 (May 2002)
Influence of Hot-Mix Asphalt Parameters on the Correction Factors of the Ignition Oven Test
The ignition oven method has been gaining popularity because of its applicability to both laboratory and field conditions, its nondependency on chemicals, and its ability to evaluate both binder content and aggregate gradations. However, the use of this method requires the careful determination of correction factors for both binder content and aggregate gradations. The need for such correction factors stems from the fact that most aggregates experience a certain level of weight loss as they are subjected to elevated temperatures. These weight losses must be accounted for in order to accurately determine the binder content and aggregate gradation of HMA mixtures. It is well accepted that the most important step of the ignition oven test is the determination of an accurate correction factor. The implementation of the ignition oven method requires the highway agency to assess the performance of the local materials with the test procedure and to identify the mixture parameters that significantly impact the determined correction factor. In preparation for the implementation of the ignition oven test, the Nevada Department of Transportation (NDOT) conducted an extensive laboratory testing program to assess the impact of the various mix parameters on the determination of the correction factors. The experiment included aggregate source, binder type, lime, and testing temperature. This paper analyzes the data generated from the NDOT experiment and evaluates the impact of each of the considered factors on the correction factor. In summary, the analysis of the data generated in the NDOT experiment showed that the aggregate source and the addition of lime have the most significant impact on the determined correction factor followed by the temperature and binder type. However, if during a field project the binder or the method of lime application changes, this change would not require the determination of a new correction factor. The data also showed that the blank aggregate method would generate correction factors that are less variable than the known asphalt content method.