Author, as appears in the article.: Amaris C; Alvarez ME; Vallès M; Bourouis M

Department: Enginyeria Mecànica

URV's Author/s: Bourouis Chebata, Mahmoud / Vallès Rasquera, Joan Manel

Keywords: Water Semi-empirical model Plus lithium-nitrate Plate heat exchanger Nonequilibrium phenomenological theory Nh3/lino3 Mass-transfer Lithium nitrate Heat-transfer Heat and mass transfer correlations Falling film Bubble absorption Bubble absorber Artificial neural networks Ammonia absorption process Ammonia Advanced surfaces

Abstract: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. In this study, ammonia vapor absorption with NH3/LiNO3 was assessed using correlations derived from a semi-empirical model, and artificial neural networks (ANNs). The absorption process was studied in an H-type corrugated plate absorber working in bubble mode under the conditions of an absorption chiller machine driven by low-temperature heat sources. The semi-empirical model is based on discretized heat and mass balances, and heat and mass transfer correlations, proposed and developed from experimental data. The ANN model consists of five trained artificial neurons, six inputs (inlet flows and temperatures, solution pressure, and concentration), and three outputs (absorption mass flux, and solution heat and mass transfer coefficients). The semi-empirical model allows estimation of temperatures and concentration along the absorber, in addition to overall heat and mass transfer. Furthermore, the ANN design estimates overall heat and mass transfer without the need for internal details of the absorption phenomenon and thermophysical properties. Results show that the semi-empirical model predicts the absorption mass flux and heat flow with maximum errors of 15.8% and 12.5%, respectively. Maximum errors of the ANN model are 10.8% and 11.3% for the mass flux and thermal load, respectively.

Thematic Areas: Zootecnia / recursos pesqueiros Renewable energy, sustainability and the environment Interdisciplinar General computer science Fuel technology Engineering (miscellaneous) Engenharias iv Engenharias iii Engenharias ii Energy engineering and power technology Energy (miscellaneous) Energy & fuels Electrical and electronic engineering Economia Control and optimization Ciências ambientais Ciências agrárias i Ciência da computação Building and construction Biotecnología Biodiversidade Astronomia / física

licence for use: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 19961073

Author's mail: manel.valles@urv.cat mahmoud.bourouis@urv.cat

Author identifier: 0000-0002-0748-1287 0000-0003-2476-5967

Record's date: 2023-02-23

Papper version: info:eu-repo/semantics/publishedVersion

Link to the original source: https://www.mdpi.com/1996-1073/13/17/4313

Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/

Papper original source: Energies. 13 (17):

APA: Amaris C; Alvarez ME; Vallès M; Bourouis M (2020). Performance assessment of an NH3/LiNO3 bubble plate absorber applying a semi-empirical model and artificial neural networks. Energies, 13(17), -. DOI: 10.3390/en13174313

Article's DOI: 10.3390/en13174313

Entity: Universitat Rovira i Virgili

Journal publication year: 2020

Publication Type: Journal Publications