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About the Customer

ArcelorMittal is a multinational steel manufacturing company, headquartered in Luxembourg. It is the world's largest steel producer, with operations in more than 60 countries. The company produces a wide range of steel products for various industries, including construction, automotive, energy, packaging, and household appliances. ArcelorMittal has a strong commitment to sustainability and operates with a focus on reducing its environmental impact. The company invests heavily in research and development to drive innovation in the steel industry.

Their Challenge

To achieve a particle size that is feasible to be processed, fine iron ores are agglomerated, fired on the sinter strand, and cooled down in the sinter-cooler before being crushed and sent to the blast furnace. During the charging of the hot material into the sinter cooler, particle separation can occur, which can lead to problems such as fire issues on conveyor belts and sinter quality issues.

To investigate the segregation patterns, and in particular the impact of particle sizes and the effect of the filling ratio on the segregation patterns in the trolleys of the sinter strand, the R&D team had to find a suitable simulation method in order to analyze and optimize the particle flow. Since simulating granular flows in a large system compared to the particle size is complex and time-consuming, the R&D team had to set up a modelling strategy that allowed for a good balance between computational efficiency and physical realism.

Our Solution

ArcelorMittal R&D used the high-performance software for granular material simulation solution Altair EDEM to simulate the granular flows in the charging chute. Providing pre-calibrated material models, EDEM enabled the engineers to create and calibrate their EDEM model to match the physical experiments.

First, the engineers analyzed the separation patterns in the trolleys of the sinter strand which were in good alignment with the experimental measurements at the plant. To find out whether finer materials would change the separation pattern, they ran a sensitivity study using different particle sizes. The results of this analysis revealed that the size of the particles had no effect on the segparation patterns. In addition, to define the best charging practices with the DEM model to ensure even distribution, the team studied the effect of the filling ratio on granular flow patterns.

The analysis of the flow pattern of coarse and fine particles showed that a large filling ratio leads to an even distribution while a low filling ratio has a uneven effect. Using the results of their studies, the engineers then virtually tested different charging chute scenarios to find a design that meets all requirements regarding capacity and mechanical resistance. 

DEM Simulation ProjectionFig 1: DEM simulation of a sinter cooler charging chute system


The DEM simulation provided valuable insight into the granular flow in the charging chute
and separation patterns, which historically, can be difficult and sometimes impossible to measure in experiments. Thanks to EDEM’s fast and scalable compute performance, ArcelorMittal R&D was able to simulate the complex particle system of the sinter cooler charging system and validate with plant data for separation. The DEM model provided results that correlated well with the segregation measurements.

Building a DEM particle model for agglomerate particles by a calibration procedure helped
ArcelorMittal to define the best charging practices and change the charging chute design that acts
on the segregation pattern in the trolleys. 


EDEM Representation

"EDEM enabled us to understand the material behavior and the charging
system – and consequently, find an optimal design to improve sinter cooling efficiency.”

Edouard Izard, Research and
Development, ArcelorMittal