Granular reactive flows are found in many industrial and natural processes. However, despite advances in modern computers, the simulation of such systems involving millions of particles is prohibitively expensive in terms of computational time. Therefore, the main objective of this work is to find novel algorithms to reduce it significantly. Many researchers, such as Bednarek [1] and Lichtenegger [2] have looked into this issue and have developed different extrapolation methods based on the pseudo-periodic properties of industrial processes. Bednarek applied an original algorithm to a conical screw mixer containing dry powders. His extrapolated results agreed with the full DEM results by decreasing CPU time to a factor of 105 . However, this only allowed the simulation of the mixing of similar powders. The main idea of this contribution is to extend the approach of Bednarek to take into account collision of particles along they trajectories. The principle of the method is to run a short DEM simulation for one period and then use our extrapolation algorithm to predict the long time evolution of the system. The first example is the extrapolation of heat conduction in a rotating drum. The results are very similar to the original DEM simulation (error <3%) with a decrease of the CPU time by a factor of 500. The next step will be the generalization of the algorithm for the extrapolation of heat transfer/chemical reaction in CFD/DEM simulations. [1] Bednarek, Xavier, et al. "Extrapolation of DEM simulations to large time scale. Application to the mixing of powder in a conical screw mixer." Chemical Engineering Science 197 (2019): 223-234 [2] Lichtenegger, Thomas, and Stefan Pirker. "Recurrence CFD–a novel approach to simulate multiphase flows with strongly separated time scales." Chemical Engineering Science 153 (2016): 394-410.