Prediction of Heap Shape in Blast Furnace Burden Distribution

Abstract

Estimation and prediction of the stock profile in the radial direction of the furnace is essential for controlling ore and coke distribution and permeability distribution. In this paper, based on experiments carried out in different scaled model of blast furnace with different material, a general purpose methodology to estimate the stock profile in blast furnace burden distribution is proposed.KEY WORDS: burden distribution; heap formation; stock level; bell less top.

Effect of the Main Feeding Belt Position on Burden Distribution during the Charging Process of Bell-less Top Blast Furnace with Two Parallel Hoppers

“…Additionally, some investigators studied the size distribution and falling point of particles by small scale experiments. [9][10][11][12][13][14][15][16][17] However, the information obtained from experiments or single particle mathematical model on size segregation and flow patterns is still limited. Therefore, more detailed work is needed in order to understand the burden distribution in the hopper and throat.…”

Investigation on the uneven distribution of different types of ores in the hopper and stock surface during the charging process of blast furnace based on discrete element method

“…Thus, the particle motion and distribution law in the hopper and the stock surface has been studied by the scholars and ironmaking workers. The research methods of particle motion and distribution law during the charging process are mainly divided into three types, physical experiment [1][2][3][4][5][6][7], single particle mathematical model [8][9][10][11][12][13][14] and discrete element method (DEM) simulation [15][16][17][18][19]. First, the cost of the physical experiment is very expensive, so it cannot be adopted as a normal research method.…”

Radar Detection-based Modeling in a Blast Furnace: a Prediction Model of Burden Surface Shape after Charging

“…To date, existing prediction models can be classified into empirical models, 3) classical force models, [4][5][6][7][8][9] neural network models 10) or models using the discrete element method (DEM). 11) Among these types of models, classical force models outperform the others in real-time online calculation scenarios, because they offer higher prediction accuracy than do empirical models; the ability to predict the entire geometric shape, unlike neural network models; and moderate computational complexities for real-time online prediction comparing with those associated with DEM models.…”

“…However, in practical cases involving multiple pitch angles of charging provided by a rotating chute, the burden surface can take on a more complex shape with multiple heaps. Recently, Nag et al 9) indicated that a single Gaussian function fits the modeling of burden radius heap shape well.…”