Evaluation of bulk material behavior control method in technological units using DEM. Part 2

Abstract

The research is dedicated to the development of special devices (capsules) that can be used to control the mining ore behavior in the technological unit in order to increase processes efficiency. In the first part of the article, the choice of the discrete element method for generating various particle trajectories in the unit (drum pelletizer) was substantiated. This part describes the specific technologies that were used to recognize the pelletizing mode. In particular, conversation of paths to sensor readings is implemented using the Matlab Sensor Fusion and Tracking Toolbox. The obtained readings were processed using two neural network classifiers (DNN and LSTM). As a result, stable models for recognizing the pelletizing modes of the unit were obtained. LSTM recognition accuracy is greater than DNN. The developed approach can be used to recognize the operating modes of other technological units. In addition, data on particles trajectories can be used to improve DEM models of technological processes. Future work consists of the capsule physical implementation and testing the recognition algorithm on a real unit.

Semi-Autogenous Wet Grinding Modeling with CFD-DEM

“…With an increase in the number of particles participating in the simulation, and with a decrease in their size, the total number of fixed contacts grows exponentially. In this regard, DEM modeling is inevitably associated with the assumptions inherent in the FEM method [25,26]. In this study, the following assumptions were made:…”

Modeling of Non-Ferrous Metallurgy Waste Disposal with the Production of Iron Silicides and Zinc Distillation

“…Industrial waste located in dumps and containing in its chemical composition heavy non-ferrous metals and various compounds of silicon, calcium, aluminum and iron has a negative impact on the environment from the point of view of ecology, in particular on public health, flora and fauna [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. However, based on its chemical composition, it is valuable and can serve as a secondary technogenic raw material for various kinds of industries, for example in the metallurgical, construction, chemical and other industries [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 …”

“…However, based on its chemical composition, it is valuable and can serve as a secondary technogenic raw material for various kinds of industries, for example in the metallurgical, construction, chemical and other industries [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ]. Thus, in Kazakhstan, in the process of extracting non-ferrous metals at a number of plants, since the 1920s and up to the present, in a number of areas, in particular, in the east Kazakhstan and Turkestan regions, there is a significant amount of clinker waste from the cultivation of various raw materials, which is now stored in dumps, occupying fertile lands and polluting the soil, surface and groundwater, the atmosphere, penetrating animal and human organisms through the migration of heavy metals along the food chain [ 9 ,…”

Risk Factors Evaluation for Monitoring of Well Drilling

“…However, for the oil and gas industry, the use of such technologies has significantly increased in recent years [11][12][13][14][15][16][17][18]. An important task of the development of the oil and gas industry in the coming years is to increase the efficiency of producing oil and gas and drilling of a well and the main impetus to the introduction of methods of ML was the fall in oil prices.…”