Torque-Based Evaluation and Predictive Modeling of Asphalt Mixture Workability Using a High-Capacity Mixing Device

This study investigates asphalt mixture workability using a high-capacity torque-based device under semi-industrial laboratory conditions. Unlike conventional laboratory-scale mixers, the proposed system accommodates batch sizes up to 15 kg, enabling more realistic simulation of plant and field mixing conditions. Torque response was monitored during the mixing of conventional, warm-mix, and RAP-containing asphalt mixtures. Predictive models were developed using stepwise regression to relate torque to mixture parameters, including temperature, RAP content, and binder type. Results indicate that RAP significantly increases mixing torque, while elevated temperatures reduce resistance to mixing. Although the developed models demonstrated moderate to good explanatory power (R2 = 0.63–0.77), they provide useful comparative insights into asphalt mixture workability rather than absolute predictions. The proposed torque-based methodology offers a practical framework for workability assessment and quality control of asphalt mixtures beyond traditional laboratory scales.