Neural network modelling of NaNO2 inversion process kinetics

• Autorzy: Piotrowski J. , Piotrowski K. , Lipowska B.
• Języki publikacji: EN

Abstrakty

EN

Modelling of a complex, heterogeneous process of sodium nitrate (III) inversion with the nitric acid (V) was carried out. The Artificial Neural Network was used for the process kinetics' numerical evaluation. The own set of experimental data was the basis for the Neural Network's training and testing. The optimal Neural Network's structure corresponds to: 4 inputs, 2 hidden layer (with adequately: 10 and 6 neurones) and 2 output neurones. The Neural Network's model correctly describes the inversion process kinetics in the following parameters' ranges: c(0NaNO2) = 0.25-0.5 mol/dm3, c(0NaNO3) = 1.5 - 3.0 mol/dm3, T = 303 - 343 K, Re(m) = 8500.

Słowa kluczowe

EN

inversion; sodium nitrate (III); nitric acid (V); Artificial Neural Networks

PL

inwersja; azotan sodowy(III); kwas azotowy (V); sztuczne sieci neuronowe; kinetyka

• Wydawca: West Pomeranian University of Technology. Publishing House
• Czasopismo: Polish Journal of Chemical Technology
• Rocznik: 2004
• Tom: Vol. 6, nr 1
• Strony: 37--41
• Opis fizyczny: Bibliogr. 20 poz., tab., rys.

Twórcy

autor

Piotrowski J.

• Department of Chemistry and Inorganic Technology, Silesian University of Technology, B. Krzywoustego 6, 44-100 Gliwice

autor

Piotrowski K.

• Department of Chemical and Process Engineering, Silesian University of Technology, B. Krzywoustego 6, 44-100 Gliwice

autor

Lipowska B.

• Institute of Refractory Materials, Gliwice

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