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Nwachukwu, C.
Department of Agricultural and and Bioresources Engineering, Michael Okpara University of Agriculture, Umudike, P.M.B 7267 Umuahia, Abia State, Nigeria
Eke, A. B.
Department of Agricultural and and Bioresources Engineering, Michael Okpara University of Agriculture, Umudike, P.M.B 7267 Umuahia, Abia State, Nigeria
Ndukwu, M. C.
Department of Agricultural and and Bioresources Engineering, Michael Okpara University of Agriculture, Umudike, P.M.B 7267 Umuahia, Abia State, Nigeria
ABSTRACT
This work set out to develop, fit, and validate
predictive models for the cleaning efficiency of a multigrain cleaning machine.
The study aimed to integrate dimensional analysis with regression fitting to
derive physically consistent models for predicting cleaning efficiency at varying
moisture content of the product. Cleaning efficiency was modelled as a function
of feed rate, air speed, and sieve inclination angle. The model was validated
using an existing multigrain cleaner with sorghum as the validating crop. The
cleaning efficiency model was developed using dimensional analysis and
regression fitting, yielding constants kc = 0.987, a = 0.042, b = 0.018, and c
= 0.005. These values revealed that the aerodynamic group exerted the strongest
influence, followed by mechanical effects, while sieve inclination contributed
minimally to the overall results. Statistical diagnostics confirmed the
adequacy of the model, with R² = 0.92 and RMSE = 0.0009, equivalent to less
than ±0.15% deviation.
Keywords: Multigrain cleaning machine, Dimensional analysis, Predictive modelling, Sieve inclination, Aerodynamic effects tance
https://doi.org/10.33922/j.ujet_v12i1_4
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Published
Saturday, February 21, 2026
Issue
Vol. 12, No. 1, March 2026
Article Section
GENERAL
The contents of the articles are the sole opinion of the author(s) and not of UJET.
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