Testing Stochastic Models for Simulating the Seeds Separation Process on the Sieves of a Cleaning System, and a Comparison with Experimental Data

A common method of analyzing experimental data is to determine the distributional model which best describes the process under study. In this paper, theoretical statistical models discussed by Tarcolea et al. (2008) are corroborated with data for the cleaning system of a combine harvester, data obtained experimentally in laboratory conditions. The purpose of this paper is to illustrate how some of the continuous distributions can be used for describing the variation separation intensity of seeds on sieve length. The Pearson coefficients show that some curves are far from the normal distribution, and better fits can be obtained with other distributions which can describe more adequately different degrees of skewness and peakedness of the curves. The considered probability laws are: normal, gamma, Weibull and beta distributions. The best results were obtained with gamma and beta distributions, since, for example, the values of the correlation coefficient R2 are in the most of the corresponding cases close to 1

EXPERIMENTATION METHODOLOGY FOR SEEDS SEPARATION WITH PLAN SIEVE AND IN AIRFLOW

After the harvesting process, the material obtained must undergo cleaning andsorting operations to remove foreign bodies, which determines the increase of purity so that it can meet the quality requirements imposed. In order to achieve these operations, the most used machines are the ones with flat sieves and with airflow. Thus, in this paper was aimed to develop the working methodology for researching the process of separating wheat seeds on the plane sieves and the airflow of the TC600 Combined Separator in order to optimize the performance of this machine

Development of some Models for Assessment the Dynamic Migration Processes of Phosphates in Soil Columns

Due to complexity of phosphate (P) migration in soil columns, the problem of theoretical approach of modeling the process is specially difficult. So, numerous semiempirical models based on admission of simplifying assumptions were developed, some of them being apart from the real phenomenon. In this paper are presented the breakthrough curves, the phosphate (P) usage degree in soil, based on a dynamic study, realised in order to determine phosphate sorption rate on the granules of two soil types (cambic chernozem and psamosoil) from Romania. Due to random character of the process, which is influenced by many naturally variable factors, this can be addressed from stochastic point of view. Experimental data regarding phosphate migration in soil column evolution process are represented like curves with sigmoid profile. Based on this observation, Rosin- Rammler and Schuhman sigmoid profile curves, known models and logistic type equations were used as simulation models representing phosphate transport and sorption kinetics for laboratory experiments in columns. Testing the models with the experimental data resulted with the conclusion that the most appropriate models describing the process of phosphate migration in soil columns are Rosin-Rammler and logistic type equation, C = 1-exp(-btn) and C = [1+exp(α+βt)]-1, (C – relative concentration; t – time; b, n, α, β - constant coefficients determined from experimental data by non-linear regression) for which the correlation coefficient is R2 ≥ 0.983 for both types of soil