The properties of the milled mixture of sugar cane change greatly during the milling process. The evolution of its properties was modeled using three‐dimensional simulation method of the modified Drucker–Prager Cap model. Parameters for the model were determined by dynamic compression tests and simulated contrast test and employed to analyze the changes of roll load, roll torque, the maximum speed of sugar juice, stress, pore pressure, and the maximum void ratio under compression ratios of 1.5–3.5, blanket thicknesses of 40–140 mm, roll diameters of 700–1000 mm, and roll surface speeds of 0.1–0.5 m/s. The following results have been found: compression ratio plays the leading role in stress, pore pressure, roll load, and roll torque which increase with it; blanket thickness is of primary importance for maximum void ratio which increases with it; and roll surface speed has the most obvious effect on maximum sugar juice speed which increases with it. The method of this paper might provide a more accurate prediction for the optimization of these important parameters during the milling process of sugar cane.
Practical applications
The properties of the milled mixture of sugar cane change greatly during the milling process. However, the material properties for the constitutive model adopted by the researchers were the mean values of those measured. As a result, the predicted results obtained by the model based on the average values of these parameters are different from those obtained by the actual tests. We evolved the law of variation of parameters and adopted a three‐dimensional simulation method of the modified Drucker–Prager Cap model to the milling process of sugar cane. Our results show compression ratio is most important for stress, pore pressure, roll load, and roll torque which increase with it; blanket thickness and roll surface speed are of primary importance for maximum void ratio and the most obvious effect on maximum sugar juice speed which increases with them. Information presented here can serve as a guidance for a more accurate prediction for the optimization of these important parameters during the milling process of sugar cane.