Estimation of (vapour+liquid) equilibrium of binary systems (tert-butanol+2-ethyl-1-hexanol) and (n-butanol+2-ethyl-1-hexanol) using an artificial neural network

Autor:	Hossein Ghanadzadeh, HamidReza Ahmadifar, Hossein Ghanadzadeh Gilani
Rok vydání:	2008
Předmět:	Artificial neural network Atmospheric pressure Butanol Binary number Thermodynamics Atmospheric temperature range Atomic and Molecular Physics and Optics chemistry.chemical_compound chemistry n-Butanol General Materials Science 1-Hexanol Binary system Physical and Theoretical Chemistry
Zdroj:	The Journal of Chemical Thermodynamics. 40:1152-1156
ISSN:	0021-9614
DOI:	10.1016/j.jct.2008.02.011
Popis:	(Vapour + liquid) equilibrium (VLE) data are important for designing and modelling of process equipment. Since it is not always possible to carry out experiments at all possible temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of VLE. In this paper, an alternate tool, i.e. the artificial neural network technique has been applied for estimation of VLE for the binary systems viz. (tert-butanol + 2-ethyl-1-hexanol) and (n-butanol + 2-ethyl-1-hexanol). The temperature range over which these models are valid is (353.2 to 458.2) K at atmospheric pressure. The average absolute deviation for the temperature output was in range 2% to 3.3%. The results were then compared with experimental data.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::04b3ef72d8977e7fbfadc7140f53b8fc https://doi.org/10.1016/j.jct.2008.02.011 Zobrazit plný text záznamu Full Text from ScienceDirect