alexa On the Estimation of the Density of Brine with an Extensive Range of Different Salts Compositions and Concentrations | OMICS International| Abstract

ISSN: 2157-7544

Journal of Thermodynamics & Catalysis

  • Review Article   
  • J Thermodyn Catal 2016, Vol 7(2): 167
  • DOI: 10.4172/2157-7544.1000167

On the Estimation of the Density of Brine with an Extensive Range of Different Salts Compositions and Concentrations

Tatar A1, Halali MA1* and Mohammadi AH2,3,4*
1Young Researchers and Elite Club, North Tehran Branch, Islamic Azad University, Tehran, Iran
2Institut de Recherche en Génie Chimique et Pétrolier (IRGCP), Paris, France
3Thermodynamics Research Unit, School of Engineering, University of Kwazulu-Natal, Howard College Campus, Durban, South Africa
4Département de Génie des Mines, de la Métallurgie et des Matériaux, Faculté des Sciences et de Génie, Université Laval, Québec (QC), G1V 0A6, Canada
*Corresponding Author (s) : Halali MA, Young Researchers and Elite Club, North Tehran Branch, Islamic Azad University, Tehran, Iran, Email: [email protected]
Mohammadi AH, Institut de Recherche en Génie Chimique et Pétrolier (IRGCP), Paris, France, Email: [email protected]

Received Date: May 01, 2016 / Accepted Date: May 20, 2016 / Published Date: May 26, 2016

Abstract

Accurate determination of brine density is crucial for an efficient designing of various systems through where brine take an undeniable part. The importance of determining brine density is well corroborated by recent ongoing research surge in this scope. Despite existence of several experimental and empirical approaches, a reliable and robust model seems to be requisite for precise determination of brine density. In regard to high performance and great robustness of soft computing approaches for unraveling science and engineering problems, this article proposes LS-SVM and MLP-NN models to determine the brine density. Both models are developed over 1868 data points including both natural and synthetic brines. The proposed models take account an extensive range of input parameters such as temperature, pressure, and concentration. The developed models can significantly estimate the target values with respect to high values of R2, which are 0.999999 and 1.000000 for MLP-NN and LS-SVM models, respectively. Considering high accuracy and swiftness of proposed models, they can be great assets to science and engineering scopes.

Keywords: LS-SVM; MLP-NN; Model; Brine density; Natural and synthetic brine.

Citation: Tatar A, Halali MA, Mohammadi AH (2016) On the Estimation of the Density of Brine with an Extensive Range of Different Salts Compositions and Concentrations. J Thermodyn Catal 7: 167. Doi: 10.4172/2157-7544.1000167

Copyright: © 2016 Tatar A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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