Asphalt Air Voids Research Articles

Comparative Study of 2D Petrographic and 3D X-ray Tomography Investigations of Air Voids in Asphalt.

Knowledge of the exact composition of building materials (aggregate, binder, air voids, etc.) is essential for the further development of more resistant and sustainable building materials. In numerous scientific studies, the material behavior of asphalt is tested using mechanical methods. Here, the overall material behavior is determined (bitumen, air voids, aggregate). With the advent of imaging techniques, it is becoming possible to determine the individual constituents separately and perform a more detailed analysis of their location, shape and composition. Three-dimensional and two-dimensional methods are available for this purpose. For this study, two different types of asphalt (porous asphalt and asphalt concrete) were analyzed using 3D X-ray computed tomography and asphalt petrology as 2D methods; the results of both investigations are compared. The objective of this study is to determine whether the 2D method provides suitable results for the microstructural analysis of asphalt samples and how the results differ from those studied by the 3D method. The comparison shows that both methods can be used to analyze voids in asphalt samples. The 2D method provides valuable insight into the distribution of voids in a sample. In addition to the distribution of voids within a 2D section, the 2D method can also be used to make some structural statements about the location and structure of the voids in the 2D plane. The X-ray computed tomography method allows more complex analyses of the pore structure because of the third direction (3D). In addition, the 3D method provides more data, so that the pore structure can be described even more precisely, and the pore size (length, width, height) can be mapped and analyzed with a high degree of accuracy.

SEM Analysis on Electron Arc Furnace Dust (EAFD) and EAFD-Asphalt Mixture

Electric Arc Furnace Dust (EAFD) is a by-product of steelmaking industry which has been classified as hazardous. The considerable amounts produced per ton of steel, estimated by 15-20 kg/ton, make it a serious environmental problem that should be addressed. One of the solution scenarios is the use of Solidification/stabilization technology and one of potential candidates is the asphalt as a widely used material in road construction. This paper had an insight view on the microstructure of EAFD and its mixture with asphalt using the scanning electron microscopy (SEM). The scanning results showed that the EAFD small particles fill the air voids in asphalt and those of bigger size get attached to the surface. This was confirmed by the specific gravity and penetration tests.

Effects of Nonnormal Distributions on Highway Construction Acceptance Pay Factor Calculation

Percent within limits (PWL) is a commonly used quality control/quality assurance measure of highway pavement materials and construction, and it is a popular index for adjusting pay factors. However, PWL is based on the assumption of normal distribution of quality characteristics (e.g., concrete compressive strength and asphalt air voids). Skewness and kurtosis, which are common forms of statistical nonnormal distributions, can potentially bias the acceptance pay factor calculations. To examine this potential pay bias, simulations were performed to investigate the magnitude and the direction (overestimation or underestimation) of pay factor calculations. The study revealed that for both one-sided and two-sided specification limits, bias in pay factors not only did vary in magnitude but also reversed in direction over various ranges of PWL. These analyses showed that for a one-sided upper specification limit, on average, a positive skewness and kurtosis can underestimate the pay factor of an acceptable quality level population by 0.90%, and overestimates a rejectable quality level population by 3.8%. This leads to falsely penalizing acceptable products and rewarding bad products. The same was true for two-sided limits, which again varied based upon the percent of defective materials at the tails of the distribution. This is a very important issue because these biases in pay factors can easily upset the relative profit margins of the contractor. Furthermore, this may not be easily detectable without a detailed and sophisticated analysis as outlined in this paper. For multiple quality characteristics based pay factors, analyses showed that the combined magnitude of these biases was not linearly cumulative. Findings of the study indicate that bias in pay was higher for lots with fewer sublots and higher skewness and kurtosis.