Using FFT-based data processing techniques to characterize asphaltic concrete mixtures

Joseph E Adidhela, University of Texas at El Paso

Abstract

In many computer applications, there is a need to match (reference) two images or two curves. For referencing images, several algorithms have been developed.^ In principle, these algorithms can be also used for referencing non-image data. However, as our analysis shows, for these methods to be successful for data referencing, we must modify these methods. ^ As a case study for data referencing, we consider the problem of characterizing asphaltic concrete mixes. This problem is an important practical case of a general problem of analyzing viscoelastic materials. A natural way to test the quality of a pavement is to send signals with different frequencies through the pavement and compare the results with the signals passing through an ideal pavement. For this comparison, we must determine how, for the corresponding mixture, the elasticity E depends on the frequency f in the range from 0.1 to 105 Hz. It is very expensive to perform measurements in high frequency area (above 20 Hz). To avoid these measurements, we can use the fact that for most of these mixtures, when we change a temperature, the new dependence changes simply by scaling. Thus, instead of performing expensive measurements for different frequencies, we can measure the dependence of E on moderate frequencies f for different temperatures, and then combine the resulting curves into a single “master” curve. In this thesis, we present several algorithms that automate this “combination”. ^

Subject Area

Engineering, Civil|Computer Science

Recommended Citation

Adidhela, Joseph E, "Using FFT-based data processing techniques to characterize asphaltic concrete mixtures" (2004). ETD Collection for University of Texas, El Paso. AAIEP10774.
http://digitalcommons.utep.edu/dissertations/AAIEP10774

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