Kent Tano

Influence of Air Humidity on Drying of Individual Iron Ore Pellets

The influence of air humidity on drying is investigated at four inlet air dew points; T dp = 273, 292, 313, and 333 K. A numerical model taking into account capillary transport of liquid and internal evaporation is applied to a spherical geometry representative for an individual iron ore pellet. Drying simulations are carried out with commercial computational fluid dynamic (CFD) software and the boundary conditions are calculated from the surrounding fluid flow. The results indicate that the effect of air humidity arises from the start of the first drying period, that is, the surface evaporation period, whereas the difference is reduced at the end of the period due to a prolonged stage of constant rate drying attained at high saturations. At low saturations, there is no constant drying stage because the surface becomes locally dry before the pellet temperature has stabilized at the wet bulb temperature. The magnitudes of the drying rates and moisture contents are rather similar at the time when internal drying becomes dominating (i.e., when the total surface evaporation rate is zero) for the respective dew points, yet the drying time is increased at high saturations. It was also found that the moisture gradients at the surface and inside the pellet increased with drying rate.

Simulation of convective drying of a cylindrical iron ore pellet

Purpose – The purpose of this paper is to numerically model convective drying of a two‐dimensional iron ore pellet subjected to turbulent flow.Design/methodology/approach – Simulations of the iron ore pellet drying process are carried out with commercial computational fluid dynamics software. The moisture distribution inside the pellet is calculated from a diffusion equation and drying due to evaporation at the surface is taken into account.Findings – The results show an initial warm up phase with a succeeding constant rate drying period. Constant drying rate will only be achieved if the surface temperature is constant. The falling rate period will subsequently start at the forward stagnation point when the minimum moisture content is reached, while other parts of the surface still provide enough moisture to allow surface evaporation. The phases will thus coexist for a period of time.Research limitations/implications – Owing to the complex physical processes involved in iron ore pellet drying, some parame...

Comparison of control strategies for a hematite processing plant

Abstract A model-assisted method is used for designing the control strategy for the new LKAB hematite plant in Malmberget (Sweden). Steady-state and dynamic process simulations successively help to select strategic controlled and manipulated variables, and specify the corresponding instrumentation. The control system implemented in the plant reflects the conclusions of the study. It includes an optimising control system based on Svedala–Cisa OCS© software, with a fuzzy logic expert system, a dynamic model of the process and an optimiser.

Classifying Best Access Points for Return of External Flows into Flowsheets

External flows are process streams that come from auxiliary processes or events. They are re-routed into the ordinary flowsheet since they are thought to be too valuable to be sent to any tailings pond. External flows come from multiple sources, e.g. drainage sumps, spillage thickeners, depleted products etc. Therefore, external flows may fit or not fit into an existing flowsheet depending on several factors like, flow rate frequency, dilution ratio variation, chemical and mineralogical composition, particle size or particle morphology. By using Particle Texture Analysis to investigate external flows and compare them with existing ordinary flows it is possible to pinpoint from a process mineralogy via point to what extent the external flow fits into the ordinary processing flowsheet. Results from this information category helps to reach a higher quality of process knowledge and control for every step in the concentrator. Results show that some recycled flows reconnected to the main flow are not connected to the best point. A side effectof the analysis is that some flows may be sent to later grinding stages. Thus, decreasing the load on the primary mill, and increasing the retention time.

Feature Extraction of a Strain-Gauge Signal Using Wavelets for Monitoring of a Tumbling Mill

Abstract Techniques that measure the force acting on a lifter bar, when it hits the charge inside a tumbling mill, have got an increased interest because of its direct physical relation to the behavior of the grinding charge. The possibility to combine it with discrete element modeling (DEM), which gives an opportunity to visualize the charge motion, opens new possibilities to understand the complex phenomena that takes place inside a grinding mill. In this work, a method for the measurement of the apparent filling level in a pilot ball mill, the Metso Continuous Charge Measurement system (CCM) has been used. The technique uses a strain gauge sensor, mounted on a flat steel spring, which is fitted into a recess underneath a lifter bar. Deflection of the lifter bar during every mill revolution will then give rise to a characteristic signal pattern depending on different operating conditions. In this work, which should be treated as an introduction, we show how the discrete wavelet transform can be used in multivariate calibration. It will be shown that by using the fast wavelet transform on individual signals as a pre-processing method in regression modeling on CCM measurements, good compression is achieved with almost no loss of information. The predictive ability and diagnostics of the data compressed regression model is almost the same as for the uncompressed.

New ways of optimising grinding using simulation software and new measuring techniques

Abstract Today there is a strong interest in obtaining an accurate and direct measure¬ment of mill loading. The use of direct measurement methods removes much of the uncertainty associated with the heuristic inferential methods that are now commonly employed. The Continuous Charge Monitoring System (CCM) determines the toe and shoulder of the load in the mill, and indicates its volume and the angle of repose. For a long time there has been a desire to be able to compute the behavior of the ball charge movement in a tumbling mill. With the advent of computer codes like Milisoft® and similar DEM codes that are able to compute mass movements of large amounts (i.e. many thousands) of balls or rocks, the simulation of charge dynamics has started to emerge as a real possibility of achieving a better understanding of what is actually going on inside a tumbling mill.