Development of New Spray Dust Suppression Materials in Metal Mines and Prediction of Algorithm Simulation Effect

Authors

DOI:

https://doi.org/10.4108/eetsis.6990

Keywords:

Spray Dust Suppression, Computational Fluid Dynamics, Metal Mining, Algorithm Simulation

Abstract

PROBLEM: Dust contamination in metal mining poses substantial dangers to environmental quality and human health. Modern mining operations cannot use traditional spray dust suppression methods because they are poorly adapted to changing climate conditions, low efficient, and detrimental to the environment.

INTRODUCTION: Dust pollution seriously impacts the environment and human health in metal mine operations. Traditional spray dust suppression technology has many problems, such as limited effect, environmental impact, and poor climate adaptability.

OBJECTIVES: The purpose of this article is to develop a new type of spray dust suppression material and predict its dust suppression effect through algorithm simulation. Firstly, efficient and environmentally friendly dust-reducing materials were screened, and after evaluating the dust-reducing effect under laboratory conditions, the optimal material combination was determined.

METHODS: Using computational fluid dynamics (CFD), a numerical model of the spray process was constructed to simulate the dust suppression effect of different materials under different climatic conditions.

RESULTS: The results show that the highest dust reduction efficiency of the new spray dust reduction material is more than 4.3% higher than that of the traditional material, and it shows good stability.

CONCLUSION: The new spray dust control material and its effect prediction method studied in this article provide an effective solution for dust control in metal mines, which has important theoretical value and practical application prospects.

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Published

06-11-2024

How to Cite

1.
Peng B. Development of New Spray Dust Suppression Materials in Metal Mines and Prediction of Algorithm Simulation Effect. EAI Endorsed Scal Inf Syst [Internet]. 2024 Nov. 6 [cited 2024 Dec. 9];11. Available from: https://publications.eai.eu/index.php/sis/article/view/6990

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Section

Research articles