A fluid dynamic analysis of the blast furnace trough at Tata Steel

Abstract

The non-drainable trough of 'F' blast furnace at Tata Steel has been fluid dynamically simulated by solving the Navier-Stokes equation in order to predict the velocity field near the trough bed along with other field properties so as to focus on the locations of surface wear on the trough bed. For this purpose a total length of 3.64 m, the mast wear prone zone, of the entire trough has been taken in to considerations for modeling. The modeling zone or the computational domain consists of the skimmer plate, iron dam and some portion of the runner. The modeled portion of the trough has always higher wear compared to other locations on the trough so a fluid dynamic analysis has been done for the liquid metal in this particular portion of the trough. Turbulence present in the velocity field has been taken into considerations by imbedding the K-e turbulent model to the parent differential equations for the velocity field. The entire set of partial differ-ential equations (two for the velocities, one for contin-uity and one each for the turbulent quantities k and e) have been solved by employing a strongly non-uniform stagg-ered grid through Phoenics. The predicted velocity field reveals a strong recirculation zone just behind the skimmer plate and comparatively high shear stress just after the iron dam (at the beginning of the runner). The inclination of the iron dam has been-varied starting from 90° to 35°. It has been observed that for a 35° iron dam the predicted maximum shear stress on the trough bed has a much lower value than that of the 90° iron dam. From this analysis it has been concluded that the value of the maximum shear stress on the trough bed is an important parameter contributing to the amount of refractory wear and the location of the maximum shear stress signifies the weakest zone on the trough bed which is vulnerable to wear caused by fluid shear. It has also been noticed that the present analysis has offered many qualitative trends which are in agreement with the plant observations.