STIFFNESS MODULUS PREDICTION MODEL FOR NATURAL NANO-ZEOLITE MODIFIED HRS-WC MIXTURES

Abstract

The stiffness modulus is a critical design parameters in mechanistic methods for the structural evaluation of asphalt pavements. This study aims to develop a robust prediction model for the stiffness modulus (Smix) of Hot Rolled Sheet-Wearing Course (HRS-WC) mixtures modified with natural nano-zeolite. Experimental tests were conducted using natural nano-zeolite contents ranging from 0.1% to 0.3%. The mechanical response was evaluated through Dynamic Shear Rheometer (DSR) tests for the binder and Indirect Tensile Strength (ITS) methods using the UMATTA tool for the mixtures at various temperatures. Results indicate that natural nano-zeolite modification significantly enhances the stiffness modulus of the binder compared to conventional 60/70 penetration grade asphalt, particularly by improving its elastic behavior. Statistical analysis led to the development of a predictive model: Smix = 2162.43 + 33.31 Sbit + 727.16 NZ – 23.26 VFA. The model identifies the asphalt stiffness modulus (Sbit), natural nano-zeolite content (NZ), and voids filled with asphalt (VFA) as primary independent variables. Validation results show that the predicted Smix values align closely with laboratory data, with a ratio range of 0.630 to 1.395. This study concludes that the incorporation of natural nano-zeolite at low dosages (0.1%-0.3%) produces measurable improvements in mixture stiffness modulus at WMA production temperatures. The reinforcement mechanism is interpreted as being consistent with nano-filler behavior reported in prior literature, and warrants further microstructural verification.