Hybrid nonlinear autoregressive neural network—Weibull statistical model applied to the supercritical extraction of lanolin from raw wool
Supercritical extraction of lanolin from raw wool with modified CO2 (5% ethanol) at temperatures above the melting point of lanolin (T = 36–42 ºC) is difficult to model because of the multicomponent diffusion in the liquid layer. In this work, a neural network model is proposed based on the experime...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/330068 |
| Acceso en línea: | https://hdl.handle.net/2117/330068 https://dx.doi.org/10.1007/s42452-020-03475-7 |
| Access Level: | acceso abierto |
| Palabra clave: | Lanolin Wool-fat Neural networks (Neurobiology) Genetic algorithms High pressure extraction Neural networks Genetic algorithm Weibull Lanolina Llana--Greix Xarxes neuronals (Neurobiologia) Algorismes genètics Àrees temàtiques de la UPC::Enginyeria química |
| Sumario: | Supercritical extraction of lanolin from raw wool with modified CO2 (5% ethanol) at temperatures above the melting point of lanolin (T = 36–42 ºC) is difficult to model because of the multicomponent diffusion in the liquid layer. In this work, a neural network model is proposed based on the experiments previously published by our research group. Experimentally, the extraction of a 100-cm3 packed bed of raw wool depends on five variables, i.e., temperature (60–80 ºC), pressure (120–200 bar), solvent mass flow rate (3–5 kg/h), wool packing density (127–318 kg/m3), and time (~ 1 h). A nonlinear autoregressive exogenous (5,3,1) neural network was designed and trained with the experimental data aug-mented using an empirical Weibull statistical function. This correctly predicts the lanolin breakthrough at the extractor exit with only ± 0.42% error. The simple arithmetics of neural network allows a fast optimization with Genetic Algorithm to find optimum operation conditions for the extraction process |
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