Experimental and modeling study on CO2 absorption in a cyclone scrubber by phenomenological model and neural networks

Autor:	Mariana, Ken-ichi Sumida, Takenari Takeshita, Toshihoko Satake, Shigeo Uchida, Akinori Maezawa
Rok vydání:	2004
Předmět:	Artificial neural network Meteorology Chemistry General Chemical Engineering Co2 absorption Phenomenological model Scrubber Flux Cyclone General Chemistry Mechanics Physics::Atmospheric and Oceanic Physics
Zdroj:	Korean Journal of Chemical Engineering. 21:589-594
ISSN:	1975-7220 0256-1115
DOI:	10.1007/bf02705492
Popis:	Experimental and modeling studies have been conducted on CO2 absorption in a cyclone scrubber operated at room temperature. The effects of parameters such as the initial concentration of alkali in the solution and the liquid - gas ratio on the CO2 absorbed flux were experimentally and theoretically investigated. A phenomenological model and three-layer feed-forward neural networks have been applied to estimate the CO2 absorbed flux in the cyclone scrubber. It was shown that the neural networks’ values agreed well with the experimental data, while the values by phenomenological model partly agreed with the experimental data around the initial concentration of alkali in the solution, CBo≤0.001 kmol/m3 (pH≤11).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::421936a0a79cebff291d009a26de5e26 https://doi.org/10.1007/bf02705492 Zobrazit plný text záznamu Full text from SpringerLink