Introduction

The Discrete Element Method (DEM) is a widely used tool for simulating the behavior of bulk materials of various shapes and sizes in equipment such as silos, hoppers, and transfer chutes. DEM allows the operation of the asset to be represented numerically after correlating the model and the data of the asset under analysis. This makes it possible to identify flow patterns and physical parameters that would be difficult to obtain during operation. In addition, the method also enables the study of changes in geometry and operating parameters without the need to shut down the equipment or use physical prototypes.

Case

At a customer's request, Kot Engenharia the method to perform flow analysis on an iron ore pellet cooling bed. The study aimed to identify possible causes for insufficient cooling of a segment of material along the cooler. Figure 1 shows the equipment, as well as its main components related to material flow.

Figure 1: Geometry used in the analysis and its main components. Source: Kot Collection.

Based on reports from the operating team and images obtained in the field, it was observed that at the outlet of the cooling bed, a portion of the material was not being cooled properly. As a result, it was possible to note that the high-temperature material was repeatedly found near the outer wall of the bed, as shown in Figure 2.

Figure 2: Identification of the insufficient cooling region. Source: Kot Collection.

Regarding the material used in the model, since it is not possible to collect and handle the pellets under operating conditions, the DEM model was calibrated using data for the material at room temperature. Figure 3 shows one of the views comparing the trajectory of the pellets at the furnace outlet with the trajectory of the material in the DEM model.

Figure 3: Comparison of pellet trajectories. Source: Kot Collection.

Based on the evaluation of the process and equipment, two hypotheses were developed for the range of material that was not being cooled as expected. The two possibilities considered are:

• Irregularities in the height of the material bed;
• Non-uniform porosity of the pellet bed.

The DEM model run to evaluate pellet bed formation, which can be viewed in Video 1, shows the filling stage and the start of cooler operation.

Video 1: Bed filling. Source: Kot Collection.

This model aimed to identify the height of the material bed across the width of the bed. Based on the results of the DEM analysis, it was possible to identify uniformity in height, as shown in Figure 4.

Figure 4: Height of the pellet bed in the cooler. Source: Kot Collection.

After ruling out the possibility of variations in bed height, the next hypothesis sought to evaluate the non-uniformity of the pellet bed porosity. According to customer reports and sampling data of the bulk material after the cooler, the cooling problems were related to an increase in the fraction of smaller particle sizes.

The possibility of segregation by particle size at the furnace outlet is well known, resulting in predominantly different trajectories for each pellet size and, consequently, causing the formation of a non-uniform bed. If there is a greater presence of fines in a specific region of the cooler, the air flow in this section would be impaired and, as a result, the heat exchange capacity of the pellets in this segment would also be reduced. Therefore, greater particle variability was implemented in the DEM model, following the particle size distribution ratio provided by the customer. Figure 5 shows the flow analysis in the model as a function of particle diameter.

Figure 5: Flow analysis. Source: Kot Collection.

The model with greater particle size variability indicated that particles with smaller diameters tend to fall on the outer side of the cooling bed, coinciding with the region of worst cooling of the material. Thus, the composition of the bed was evaluated, and Video 2 shows the number of particles in each radial segment of the bed. This parameter is related to the porosity of the bed, since a region with a greater number of particles implies greater filling of the volume of this section and, consequently, a smaller fraction of empty spaces.

Video 2: Particle counting. Source: Kot Collection.

Conclusion

The analysis of the pellet bed performed using a DEM model indicated that the section with the highest number of particles and, consequently, the highest porosity, coincides with the region with the worst cooling, highlighting this factor as the cause of the problems reported by the customer. By identifying the source of the problem using computational tools, Kot was able to support its customer by obtaining the information necessary to develop and apply more targeted solutions, optimizing the use of resources and enabling significant improvements in its process.

The Kot team has qualified professionals at your disposal to evaluate and perform a wide range of consulting engineering analyses. Consult our team for more information!

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