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The Support Vector Classification (SVC) model was constructed in this study by applying the near infrared (NIR) analysis technology combined with the chemometrics method to classify and distinguish 11 types of vegetable oil, including "restaurant waste oil". Partial least squares-discriminate analysis (PLS-DA) and GA-SVC classification models were constructed, respectively, after the data...
In view of effect of fluid-solid coupling on flow of oil fluids through media and effect of rheology on fluid-solid coupling, the numerical simulation models of mechanical oil expression from vegetable oil were developed. The models were solved by using of combining finite difference with finite element. The displacement experiments for extracted peanut were used to validate the models. The predicted...
The numerical simulation model of mechanical oil expression from vegetable oil was developed. It was solved by using of combining finite difference with finite element. The displacement experiment for extracted sesame was used to validate the model. As an applied example, the predictions of pore-fluid pressure dissipation and distribution were carried out. The predicted values of displacement conformed...
A prediction model of compression ratio for extruded oilseeds was developed based on improved BP neural networks. As an applied example, the predicted curves were successfully used to predict critical pressing pressures. Results indicated that the predicted values of compression ratios conformed to the measured values well for extruded cottonseed and castor been. There was a limiting compression for...
By using of combining theoretical model with empirical model, the nonlinear viscoelastic-plastic constitutive equations of soybean and cottonseed were developed on the basis of the creep test. The parameter inverse problem of constitutive model was proposed using improved particles swarm optimization. Numerical simulations of creep of soybean and cottonseed were carried out. The definition of critical...
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