On using Vandermonde polynomials and spectral methods to optimize aggregate testing

Recycled Aggregate (RA) has been used in various construction applications around the world mainly as sub-grade, roadwork and unbound materials, but not in higher-grade applications. The major barrier encountered is the variation of quality within RA, which causes lower strength, and poorer quality. This work studies the relationships among six parameters describing the characteristics of recycled aggregate: i) particle size distribution, ii) particle density, iii) porosity and absorption, iv) particle shape, v) strength and toughness, and vi) chemical composition. Samples of recycled aggregate from ten demolition sites were obtained with service life ranging from ten to forty years. One additional set of samples was specifically collected from the Tuen Mun Area 38 Recycling Plant for testing. The characteristics of these eleven sets of samples were then compared with normal aggregate samples. A Vandermonde matrix for interpolation polynomials coefficient estimation is used yielding detailed mathematical relationships between pairs of samples, which can be used to work out redundant tests. Different orders of interpolation polynomials are used for comparison, hence the best-fit equations with lowest fitting errors from different orders of polynomials can be found. Fitting error distribution is studied by using spectral methods such as power spectra and bispectrum. From that, the best equations for result estimation can be obtained. This study reveals that there is a strong correlation among those test parameters, and by measuring two of them: either "particle density" or "porosity and absorption" or "particle shape" or "strength and toughness", and "chemical content", it is sufficient to study recycled aggregate.