The hoppers are the most common structures used in storage units for agricultural products such as grains and cereals. The soybean, which is one of the most common products in Brazil spend most of their time in a hopper between the stages of picking and shipment. Problems such as damage to the hopper structures during the outflow are factors that have been the subject of studies using computational models. Computational Fluid Dynamics (CFD) has played a big role in gas-solid systems study, together with the Discrete Element Method (DEM). This method manages both fluid phase as the solid phase, which in this case is granular, through the Eulerian and Lagrangian approach. The DEM is based on the interaction between the particles and each one is separately monitored. This work aims to calibrate the parameters of the spring-dashpot model, in the granular dynamics of fluids study, which influences the contact between the soy particles in the silo. For this purpose, a comparison was made of the experimental discharge time of soybeans into a hopper, with the time resulting from 27 simulations generated by a central composite design (CCD). Through the analysis of the simulations and statistics, it was possible to identify the factors that influence whether or not the time of discharge and establish a calibration of these parameters that best describe the experimental results.
The use of solar energy as a renewable energy source has become a good sustainable alternative today and its employment has grown. Solar distillers are powered by sunlight to make the distillation process more sustainable. In this context, the present work consisted of distilling a mixture of ethanol and coconut oil with the intention of solvent reuse in future experiments, in order to make the process more economical and sustainable. For the distillation process, a two-strand solar distiller was constructed by varying three volumes of mixture to be placed for batch distillation in order to study the influence of film thickness on solvent recovery efficiency. A maximum yield of 84.2% was obtained and the optimum liquid thickness obtained through the experiments was 0.16 cm, where the highest alcohol recovery rate was obtained. The present work was satisfactory in relation to the proposed objectives, presenting a completely sustainable process and without energy expenditure.
The fertilizer industry is becoming increasingly essential for the future of mankind as the world population continues to grow. In order for the food production rate to meet the increasing food demand, the available tillable areas need to be more productive, which can be achieved through the use of fertilizers. In this work, we present three MILP production scheduling approaches for addressing a typical phosphate fertilizer problem, comprising continuous tasks as well as short and lengthy batch tasks. The scheduling problem is also featured as presenting mixed storage policies and sequencedependent changeover times. All proposed formulations are based on a continuous singletime grid. In the first approach, batch tasks are allowed to freely take place over multiple time slots. In the second approach, batch tasks span a pre-defined number of time slots, and in the third hybrid approach, short batch tasks are allowed to freely take place over multiple time slots, while lengthy batch tasks span a pre-defined number of time slots. In all approaches, continuous tasks are assigned to a single time slot. A discrete time-based formulation is also used as a baseline comparison. It is verified that the first approach quickly becomes intractable as the number of time slots is increased. The second approach requires trial-and-error regarding the fixed number of time slots used for short batch tasks despite the excellent computational performance. Ultimately, the hybrid approach enables finding the optimal production schedule for a month scheduling horizon in approximately 4 CPU minutes without having to run multiple problem instances.
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