Abstract
This paper presents a new approach to characterisation of asphalt mixtures constitutive models, with application to pavement structures. It is well-known fact that temperature, frequency and time of loading have a great influence on the mechanical properties of bituminous mixtures. For this reason, the properties are usually presented in the frequency domain as complex numbers having real and imaginary parts. This convenient representation in terms of complex modulus and phase angle leads to the dynamic modulus master curve. The effective use of the theory of linear viscoelasticity to characterise constitutive model of asphaltic material is shown in this paper. Viscoelastic constitutive model is represented by a combination of rheological schemes, and its identification is based on both laboratory tests results and mixture composition. The temperature–frequency or temperature–time superposition principle being applied in order to produce master curves of mechanical properties is illustrated with real experimental data. Further, the process of identification of Huet–Sayegh parameters is carried out using best-fitting methods implemented in MATLAB. Fractional rheological model is used as it needs only a small number of elements to fully characterise the response of asphalt materials.
Highlights
Since asphalt mixtures are viscoelastic materials, the operating conditions, such as velocity of the travelling load and pavement temperature, have a great influence on the strain state (Graczyk 2010)
The same idea can be applied to the creep tests where the reduced variables method allows for the visualisation of all the experiments in a single creep master curve covering all times of loadings
The method of reduced variables is known as the temperature–frequency or the temperature–time superposition principle (TTSP) (Kim 2009; Wang 2010)
Summary
Since asphalt mixtures are viscoelastic materials, the operating conditions, such as velocity of the travelling load and pavement temperature, have a great influence on the strain state (Graczyk 2010). These conditions may vary within a large range (Rafalski 2007). The identification of material parameters is essential (Radziszewski et al 2014). It can be done based on laboratory tests or by using an identification procedure proposed by Zbiciak et al (2017).
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