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Using the methods of geostatic function and Monte Carlo in estimating the randomness of distribution of a two-component granular mixture during the flow mixing

100%

Krolczyk J., Tukiendorf M.

Electronic Journal of Polish Agricultural Universities. Series Agricultural Engineering

2005

tom 08

nr 4

Modelling of quality changes in a multicomponent granular mixture during mixing

86%

Krolczyk J., Matuszek D., Tukiendorf M.

Electronic Journal of Polish Agricultural Universities. Series Agricultural Engineering

2010

tom 13

nr 1

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Modelling selected parameters of granular elements in the mixing process

86%

Matuszek D.

International Agrophysics

2015

tom 29

nr 1

This paper presents the effects of mixing non-homogeneous bicomponent granular structures by the flow method with the use of an inverted cone insert as a supporting element. The analysis of homogeneity of mixtures after 10 consecutive flows was carried out based on computer image analysis. Based on these tests, the use of a nonlinear regression for the mo-delling of two selected parameters of the process was proposed. Spatial dependence was described by the relation between the va-riance of the tracer distribution (dependent variable) and density ratio of the mixed components, and the diameter of the cone insert used (independent variables). The mathematical description was made with the use of a ‘nonlinear regression’ module. The results obtained in these tests proved that the use of supporting insert improves the degree of mixability of granular materials. The two-dimensional model in the form of a quadratic function may be a for-mula for describing the influence of selected parameters on the homogeneity of a granulate mixture before the beginning of the mixing process.

Ograniczanie wyników

2 Electronic Journal of Polish Agricultural Universities. Series Agricultural Engineering

1 International Agrophysics

2 Krolczyk J.

2 Matuszek D.

2 Tukiendorf M.

1 2015

1 2010

1 2005

Wyniki wyszukiwania

Using the methods of geostatic function and Monte Carlo in estimating the randomness of distribution of a two-component granular mixture during the flow mixing

Modelling of quality changes in a multicomponent granular mixture during mixing

Modelling selected parameters of granular elements in the mixing process