At a large copper smelter plant, the productivity of a smelting furnace and the quality of the product decreased dramatically. Encata carried out thorough multiphysics processes modeling, which gave our customers the information they needed to create a plan for plant modernization.
Deeptech & Sciences
1 → 9
The core challenges of the project:
The issue necessitated specific, in-depth knowledge of raw materials, technologies used, intermediate and by-products.
The project had to be finished within a short timeframe of nine months.
The processes of mass, heat, and phase transitions had to be combined in the computer models.
The computational grid had more than 5 million elements, therefore standard PC power was insufficient to obtain accurate results in a reasonable amount of time.
Lack of comprehensive information on the characteristics of the intermediate products and the inability of carrying out the experiment
Computational Fluid Dynamics;
Finite Element Analysis;
EnCata offers comprehensive hardware and IoT product development services at a fraction of the cost
• R&D + design + manufacturing under ONE roof • Scale up and down your team • Intergrated hardware + software development • New technologies and research
For the first 3 weeks of the project, our team was not involved in modeling and design. We looked at the technological process itself and characteristics of the products created during its various stages. Our objective was not to fully comprehend the furnace process, but to dissect it into its constituent parts and focus solely on those that affected productivity.
The customer's losses from production downtime were directly related to the project duration. As a result, the team had to make trade-offs between the tasks. The utmost importance was given to the procedures that directly affected the final simulation model. For instance, the calculation of the temperature field was used to build the gas circuit instead of modeling sulfate corrosion. The areas where there was a risk of sulfate corrosion were determined through the temperature field analysis.
Submodeling helped us shorten the calculation time. We modeled the necessary area separately.As a result of the calculation, we determined the geometry of the structural elements of the furnace and established the geometry for the left and right convection shafts, the furnace uptake, and the furnace.
Understanding the technological processes that occur in a specific furnace area allowed us to simplify the calculating geometry. For example, just part of the basic geometry was analyzed when modeling the hydrodynamics of melt bubbling. The boundaries separating the calculating area from neighboring recurring areas were defined as symmetry boundaries. By simplifying calculations, we sped up modeling while maintaining calculation accuracy.
A research supercomputer was utilized for the majority of simulation runs since the size of the furnace (length 21 meters and height of the melting shop 9 meters) and tuyeres (diameter 0.2 m) blowing the gas mixture at a near-sonic speed precluded utilizing normal methods of model development. About 50 iterations were performed for the main model. For further models, our team performed a great number of tiny iterations.
The combination of heat and mass transfer processes with phase transitions is not recorded by sensors during furnace operation and is also little studied by the scientific community. Therefore, the impossibility of conducting a real experiment of boiling processes was expected. The solution was to determine the required parameters through process simulation. For instance, to gauge the intensity of melt spattering in the furnace, we assessed the average quantity of spattered slag in the control zone above the melt during the simulation.
We built a parametric validated model which describes the processes that occur during copper concentrates processing in Vanyukov furnace. They are:
thermal → heat transfer from molten copper to the environment;
hydrodynamic → the flow of molten copper and its bubbling;
aerodynamic → movement of gases and vapors inside the copper smelting furnace.
The furnace manufacturers received the findings of EnCata’s research. The plant used the research findings and therefore improved the technological process' efficiency.