The vertical layered cooling process and multi-objective optimization design of gas–solid heat transfer process in sinter

ABSTRACT

A vertical layered cooling process is developed to get more uniform cooling and higher heat transfer efficiency when compared with the circular-type and vertical integrated sinter cooling processes in this work, which has been demonstrated by the example. Based on the vertical layered cooling process, the maximum temperature of the cooled sinter and the minimum waste heat recovery is treated as two objective parameters for the multi-objective optimization design. The operating parameters influencing the sinter temperature and waste heat recovery are determined at first. Then, an accurate metamodel is established based on the Latin hypercube sampling technique and radial basis function neural network (RBFNN) approach. Finally, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to iterate the accurate metamodel and acquire the Pareto frontier for acquiring the optimal combinations of the objective parameters. Analysis results are demonstrated to be of great significance for practical engineering applications.

KEYWORDS:

• Sinter cooler
• porous media
• countercurrent moving bed
• cooling effect
• heat transfer efficiency
• waste heat recovery
• double-energy equation
• multi-objective optimization

Acknowledgements

This work is supported by National Key R & D Program of China (2017YFB1002704), State Key Laboratory of Process Automation in Mining & Metallurgy and Beijing Key Laboratory of Process Automation in Mining & Metallurgy (BGRIMM-KZSKL-2018-05) and National Science Foundation of China (11872177).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Key R&D Program of China [grant number 2017YFB1002704]; State Key Laboratory of Process Automation in Mining & Metallurgy and Beijing Key Laboratory of Process Automation in Mining & Metallurgy: [Grant Number BGRIMM-KZSKL-2018-05]; National Science Foundation of China [grant number 11872177].