Issue |
E3S Web Conf.
Volume 175, 2020
XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
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Article Number | 05016 | |
Number of page(s) | 9 | |
Section | Agricultural Machinery | |
DOI | https://doi.org/10.1051/e3sconf/202017505016 | |
Published online | 29 June 2020 |
Calculation of the throwing angle of a fertilizer centrifugal device as functions of random coordinates of feeding point
1
Azov-Black Sea Engineering Institute of Don State Agrarian University, 21, Lenina, 347740, Zernograd, Russia
2
Don State Technical University, Gagarin sq., 1, 344003, Rostov-on-Don, Russia
3
Supercomputers and Neurocomputers Research Center, 106, lane Italian, 347900, Taganrog, Russia
4
Southern Federal University, lane Italian, 106, 347900, Taganrog, Russia
* Corresponding author: lusya306@yandex.ru
Liquid fertilizers fed into centrifugal device are spread along angle and radius of feed under action of blades. This article describes how to calculate throwing angular characteristics using Mathcad. The package consists of four programs. Program Mf is intended for calculation of probability density of supply point coordinates under assumption of bivariant normal distribution of system r, γ, which are specified in the form of vectors. The result of the calculation is displayed as matrix Mf. The program Mα calculates the throwing angle for all combinations r, γ.. To calculate the throwing angle, the method of solving differential equations of particle movement along the blade of the device with input data was used: Radius of the disk R, angular speed ω, coefficient of friction of fertilizers on the blade f. The program Ms extracts from the matrix Mf elements Corresponding to a throw angle less than a given number A. The program F (A) sums the elements of the matrix Ms. We obtained the values of the throw angle distribution function by multiplying the resulting sum by the intervals of vectors r and γ. The calculated throwing angle distribution function is approximated by the standard normal distribution function.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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