Two-Parameter Probabilistic Model and Experimental Research on Micron Particle Deposition

The deposition of micron particles in gas pipelines has always been an important problem in ultra-clean ventilation technology in the modern laser fusion, precision electronics, aerospace, and biomedical fields. Combining the mathematical expression of the migration, collision, and deposition of mic...

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Veröffentlicht in:Applied sciences 2024-07, Vol.14 (14), p.6200
Hauptverfasser: Niu, Chenchen, Zhou, Zhen, Qi, Jia, Yang, Xu
Format: Artikel
Sprache:eng
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Zusammenfassung:The deposition of micron particles in gas pipelines has always been an important problem in ultra-clean ventilation technology in the modern laser fusion, precision electronics, aerospace, and biomedical fields. Combining the mathematical expression of the migration, collision, and deposition of micron particles in a gas pipeline with a simulation of flow fields, a two-parameter particle probability deposition model based on vinl, θcr and collision probability coefficient PP is established, and the distribution law of particle deposition, considering two deposition targets of the pipe wall and deposition layer, is given. Combined with an experiment on particle migration and deposition in a gas pipeline, an interpretation and verification of the particle deposition distribution law are given, and the difference between the model and experiment is discussed through particle deposition efficiency mass distribution. Studies have shown the following: Under the premise of two kinds of deposition targets, different particle sizes in the gas pipeline present different deposition laws; the deposit morphology is a spot deposit of 10 µm particles and a flake deposit of 40 µm particles; the deposit position shows a uniform distribution and a lower wall dominance; and the deposit concentration area of 40 µm shows a more significant distribution. The results are very important for the selection and optimization of gas pipelines for clean spaces.
ISSN:2076-3417
2076-3417
DOI:10.3390/app14146200