Analysis of dust diffusion from a self-propelled peanut combine using computational fluid dynamics. (March 2022)

• Record Type: Journal Article
• Authors: Xu, Hongbo; Zhang, Peng; Hu, Zhichao; Mao, Enrong; Yan, Jianchun; Yang, Hongguang
• Is Part Of: Biosystems engineering. Volume 215(2022)
• Page Start: 104
• Page End: 114
• Publication Date: 2022-03
• Subjects: Dust diffusion -- Self-propelled peanut combine -- Size distribution -- Concentration -- Computational fluid dynamics; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2022.01.004
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Self-propelled peanut combines can significantly improve the production efficiency of peanut harvesting. However, a large quantity of dust is discharged from peanut combines, leading to detrimental environmental changes. To evaluate the diffusion and distribution of dust from a peanut combine, dust discharged from a combine was sampled using an integrated atmospheric sampler that enabled laboratory measurements of dust concentration, particle size distribution, density, and shape factors. A 3D computational fluid dynamics (CFD) model that coupled dust particles and the atmospheric flow was established. The simulation model was verified by comparing the simulated data with the measured dust concentrations on farm. The relationship between the dust discharge factors and the spatial distribution of the dust concentration was analysed using the CFD model. The results showed that an increase in the angle between the dust outlet and the ground increases both the rate of dust deposition and the dust concentration near the combine. By contrast, a reduction in the dust outlet diameter decreased the dust concentration near the combine and rate of dust deposition. Moreover, the spatial dust concentration distribution and the dust concentration discharged from the dust outlet of the combine exhibited a linear relationship. This study provides a reference for the formulation and evaluation of dust suppression schemes for self-propelled peanut combines. Highlights: Self-propelled peanut combines improve peanut harvesting production efficiency. Discharged dust emitted from self-propelled peanut combine measured. Dust distribution modelled via computational fluid dynamics. Reference data provided for dust suppression strategies. Modelling method could be extended to other farm machinery.