Traditional methodologies for quality analysis of the stone aggregates for pavements use include tests such as Los Angeles Abrasion, Density, Absorption, etc., these tests show physical properties of the stone aggregate. However, it's very difficult to analyze their performance when aggregates are mixed with asphalt. This research is intended to show the importance of analyze the affinity between aggregate and asphalt in a mechanical way, to guarantee that the asphalt mixtures perform adequately and the convenience to use additives that enhance adhesiveness in certain cases.
In addition, a decision was taken to do in the Laboratory of Materials of the Universidad Michoacana de San Nicolás de Hidalgo a complete research of the affinity that exists between a stone aggregate of the ales region of Morelia, Mexico and an asphalt type AC-20 using two types of additives in different proportions. For this analysis, the department decided to use the UCL Method (Universal Method of Characterization of Binders), because it shows in a clear and simple way the performance of different types of asphalt in combination with different aggregates. Besides, this analysis allows observing their behavior in an extensive work temperatures range that can vary from the -10° C to 60° C. These temperature ranges cover the possibilities that are presented in real conditions on the region.
It was decided to analyze a crushed material of the Municipality of Tarimbaro Michoacán that complies with all the standards to be use in asphalts mixtures, but it has faced some affinity problems in different projects. This material was mixed with a conventional asphalt type AC-20 of Salamanca and also used different additives that enhance adhesiveness, well provided by a Guadalajara Jalisco Company, to see any variation of the losses in UCL Method.
The results obtained clarify that this test shows very valuable information that complements the conventional tests of asphalts characterization that will be used for pavements construction and that it's useful to take decisions regarding to choose the most adequate additives for each situation.