Firing Shchelkov and Dankov dolomites in rotary kilns with oxygen-enriched air

Refractories ◽  
1972 ◽  
Vol 13 (7-8) ◽  
pp. 500-503
Author(s):  
A. A. Shumilin ◽  
P. S. Potemkin ◽  
G. B. Beremblyum ◽  
P. E. Nakhaev ◽  
E. V. Matveev ◽  
...  
Keyword(s):  
Rotary Kilns

Problems with Refractories for Rotary Kilns and Their Factors

2019 ◽  
Vol 73 (8) ◽  
pp. 770-773
Author(s):  
Hitoshi Toda
Keyword(s):  
Rotary Kilns

Simulation of the Control System of the Coke Calcination in Tubular Rotary Kilns

2020 ◽  
Vol 2020 (13) ◽  
pp. 1600-1606
Author(s):  
T. V. Dontsova ◽  
K. G. Kozulin ◽  
T. V. Piskazhova ◽  
G. B. Danykina
Keyword(s):  
Control System ◽  
Rotary Kilns

Modeling of lime production process using artificial neural network

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolghasem Daeichian ◽  
Rana Shahramfar ◽  
Elham Heidari
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Production Process ◽  
High Energy ◽  
Ann Model ◽  
Artificial Neural ◽  
Rotary Kilns ◽  
Input Variables ◽  
Artificial Neural Network Ann ◽  
Lime Production

Abstract Lime is a significant material in many industrial processes, including steelmaking by blast furnace. Lime production through rotary kilns is a standard method in industries, yet it has depreciation, high energy consumption, and environmental pollution. A model of the lime production process can help to not only increase our knowledge and awareness but also can help reduce its disadvantages. This paper presents a black-box model by Artificial Neural Network (ANN) for the lime production process considering pre-heater, rotary kiln, and cooler parameters. To this end, actual data are collected from Zobahan Isfahan Steel Company, Iran, which consists of 746 data obtained in a duration of one year. The proposed model considers 23 input variables, predicting the amount of produced lime as an output variable. The ANN parameters such as number of hidden layers, number of neurons in each layer, activation functions, and training algorithm are optimized. Then, the sensitivity of the optimum model to the input variables is investigated. Top-three input variables are selected on the basis of one-group sensitivity analysis and their interactions are studied. Finally, an ANN model is developed considering the top-three most effective input variables. The mean square error of the proposed models with 23 and 3 inputs are equal to 0.000693 and 0.004061, respectively, which shows a high prediction capability of the two proposed models.

scholarly journals Waste incineration in rotary kilns: a new simulation combustion tool to support design and technical change

2013 ◽  
Vol 31 (7) ◽  
pp. 739-750 ◽  
Author(s):  
Francesco Lombardi ◽  
Emanuele Lategano ◽  
Stefano Cordiner ◽  
Vincenzo Torretta
Keyword(s):  
Technical Change ◽  
Waste Incineration ◽  
Support Design ◽  
Rotary Kilns

A Proposed Procedure for Identifying the Predominant Heat Transfer Modes Along the Length of Large Nickel Laterite Ore Rotary Kiln: Experimental Validation in an Industrial Process

2021 ◽  
Author(s):  
Janneth Ruiz ◽  
Antonio Ardila ◽  
Bernardo Rueda ◽  
Jorge Echeverri ◽  
Daniel Quintero ◽  
...  
Keyword(s):  
Chemical Properties ◽  
Industrial Process ◽  
Particle Model ◽  
Zone Length ◽  
Average Surface ◽  
Bed Temperature ◽  
Mineral Oxides ◽  
Rotary Kilns ◽  
Physical And Chemical ◽  
Laterite Ore

Abstract Nickel is essential in many consumer, industrial, military, transport, aerospace, marine, and architectural products due to its outstanding physical and chemical properties. This work focuses on the calcination and pre-reduction of laterite nickel ore to produce ferronickel. Ferronickel is an alloy containing nickel (about 30% wt.) and iron used for manufacturing stainless steel. Calcination and pre-reduction entail removing chemically bonded water from partially dried ore and removing oxygen from mineral oxides in the calcine. Here we combine a proprietary database with operation data of two rotary kilns and model predictions of Mean Residence Time, shell losses, intraparticle evaporation, and intraparticle temperature distribution. The kilns feature notable differences in length, inclination angle, excess air, but the predicted Mean Residence Times are similar. A fitted profile of experimental solids bed temperature represented particles surface temperature. The model considered slab-like mineral particles with surface-to-center distances of 13, 25, and 38 mm. Results show notable differences in the drying zone length and average surface-to-center temperature differences. Surface-to-center distances higher than 25 mm result in average surface-to-center temperature differences higher than 80°C. The following steps are improvements in the particle model and its coupling with the gas and wall temperature profiles.

scholarly journals A CONTRIBUTION TO THE OPTIMAL DESIGN OF RIDE-RINGS FOR INDUSTRIAL ROTARY KILNS

1985 ◽  
Vol 8 (3) ◽  
pp. 207-221
Author(s):  
HENG LONG LI ◽  
PANOS PAPALAMBROS
Keyword(s):  
Optimal Design ◽  
Rotary Kilns

CFD modeling using PDF approach for investigating the flame length in rotary kilns

2016 ◽  
Vol 52 (12) ◽  
pp. 2635-2648 ◽  
Author(s):  
H. F. Elattar ◽  
E. Specht ◽  
A. Fouda ◽  
Abdullah S. Bin-Mahfouz
Keyword(s):  
Flame Length ◽  
Cfd Modeling ◽  
Rotary Kilns
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