High moisture content in stored canola seeds can lead to spoilage and significant losses for Canadian prairie farmers. Typically, supplemental heat is used to dry stored grains when temperatures fall below 15℃ during the fall. This study aimed to investigate whether effective drying could be achieved at lower temperatures, specifically at 10℃ and 70% relative humidity (RH), with variations in airflow rates of 0.01, 0.1, and 0.35 m/s. Canola seeds, conditioned to 14% moisture content (w.b.), were placed in 1.5 m high grain columns (0.2 m inner diameter) and subjected to each of the desired airflows in the vertical direction. The columns were equipped with temperature and RH sensors to monitor the changes during drying. Each drying experiment was terminated when the RH of the top layer of the grain column reached 70%. Canola seed moisture content and germination were determined at the end of the drying. The study found that drying at 0.01 m/s airflow velocity was ineffective as the top layer had moisture content higher than safe storage levels after a run time of over 20 weeks. However, airflow velocity of 0.1 and 0.35 m/s effectively dried the stored canola to safe storage levels with run times of 84 and 10 days, respectively. The germination of the dried canola was not change from its initial germination. Therefore, grain can be dried at lower than 15oC without using supplemental heat.

Understanding roller torque is critical in predicting seed breakage and blockage in air seeders, especially when seeds are very large or irregular (e.g. chickpeas, faba beans, broad beans,…). It is currently possible using conventional DEM software to model and predict roller torque, but the high stiffness of the modelled metering roller causes over prediction of the torque required to displace the seeds from the tank to the inlet of the air conveying system. By coupling multi-body dynamics software with DEM, it is possible to model the flexibility of the flutes separating the cavities where resides the seeds during metering. The output data of these simulations can then be used by the structural analysis group (FEA) which allows to better predict the roller torque and improve the roller design and its lifetime expectancy. The properties of the seeds and roller elasticity were measured and lab data was used to validate the model.

Fields tests for bulldozer are costly, time-consuming, weather-dependent, and require highly-skilled operators to ensure providing constant volume of material pushed in front of the blade. Some methods have been developed throughout the years to predict soil volume displaced by the blade and its corresponding reaction forces.

This presentation focuses on the validation of the simulated soil volume displace during the bulldozing of material. The simulated and actual soil volumes of the pile created by the bulldozing effect are compared using Discrete-Element Method (DEM), LIDAR, and 3D scanning technologies. This volume was simulated and monitored from the beginning of each run (flat surface) until the end (maximum size soil pile). These runs were simulated with various DEM particles shapes bulldozed at 3 different ground speeds, 3 working depths and 2 blade angles, which were replicated during testing.

The top surfaces of each soil pile in front of the blade are determined from simulation and validated using data from LIDAR and 3D scanning. These surfaces are combined with the blade geometry to create hollow shell model. These virtual hollow shell surfaces are then filled with DEM realistic particles to determine the volume created by the void between the top surface, the concave blade cavity and the horizontal surface. Various properties of DEM soil particles were measured using physical material from testing site.