Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks

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 ch...

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Autores:
Amaris, Carlos
Alvarez, Maria E.
Bourouis, Mahmoud
Vallès, Manel
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7275
Acceso en línea:
https://hdl.handle.net/11323/7275
https://repositorio.cuc.edu.co/
Palabra clave:
Bubble absorption
Plate heat exchanger
Advanced surfaces
Heat and mass transfer correlations
Semi-empirical model
Artificial neural networks
Ammonia
Lithium nitrate
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_50aca4984c8548a9e711f50b971118ab
oai_identifier_str oai:repositorio.cuc.edu.co:11323/7275
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
title Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
spellingShingle Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
Bubble absorption
Plate heat exchanger
Advanced surfaces
Heat and mass transfer correlations
Semi-empirical model
Artificial neural networks
Ammonia
Lithium nitrate
title_short Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
title_full Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
title_fullStr Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
title_full_unstemmed Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
title_sort Performance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networks
dc.creator.fl_str_mv Amaris, Carlos
Alvarez, Maria E.
Bourouis, Mahmoud
Vallès, Manel
dc.contributor.author.spa.fl_str_mv Amaris, Carlos
Alvarez, Maria E.
Bourouis, Mahmoud
Vallès, Manel
dc.subject.spa.fl_str_mv Bubble absorption
Plate heat exchanger
Advanced surfaces
Heat and mass transfer correlations
Semi-empirical model
Artificial neural networks
Ammonia
Lithium nitrate
topic Bubble absorption
Plate heat exchanger
Advanced surfaces
Heat and mass transfer correlations
Semi-empirical model
Artificial neural networks
Ammonia
Lithium nitrate
description 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.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-11-12T17:32:16Z
dc.date.available.none.fl_str_mv 2020-11-12T17:32:16Z
dc.date.issued.none.fl_str_mv 2020-08-20
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
format http://purl.org/coar/resource_type/c_6501
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 1996-1073
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/7275
dc.identifier.doi.spa.fl_str_mv DOI: 10.3390/en13174313
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 1996-1073
DOI: 10.3390/en13174313
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/7275
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv 1. Amaris, C.; Vallès, M.; Bourouis, M. Vapour absorption enhancement using passive techniques for absorption cooling/heating technologies: A review. Appl. Energy 2018, 231, 826–853. [CrossRef]
2. Aggarwal, M.K.; Agarwal, R.S. Thermodynamic properties of lithium nitrate-ammonia mixtures. Int. J. Energy Res. 1986, 10, 59–68. [CrossRef]
3. Infante Ferreira, C.A. Thermodynamic and physical property data equations for ammonia-lithium nitrate and ammonia-sodium thiocyanate solutions. Sol. Energy 1984, 32, 231–236. [CrossRef]
4. Abdulateef, J.M.; Sopian, K.; Alghoul, M.A. Optimum design for solar absorption refrigeration systems and comparison of the performances using ammonia-water, ammonia-lithium nitrate and ammonia-sodium thiocyanate solutions. Int. J. Mech. Mater. Eng. 2008, 3, 17–24.
5. Infante Ferreira, C.A. Operating characteristics of NH3–LiNO3 and NH3–NaSCN absorption refrigeration machines. In Proceedings of the 19th Int. Congr. Refrig, the Hague, The Netherlands, 20–25 August 1995; pp. 321–328.
6. Ayala, R.; Frías, J.L.; Lam, L.; Heard, C.L.; Holland, F.A. Experimental assessment of an ammonia/lithium nitrate absorption cooler operated on low temperature geothermal energy. Heat Recover. Syst. CHP 1994, 14, 437–446. [CrossRef]
7. Heard, C.L.; Ayala, R.; Best, R. An experimental comparison of an absorption refrigerator using ammonia/water and ammonia/lithium nitrate. In Proceedings of the International Sorption Heat Pump Conference, Montreal, QC, Canada, 17–20 September 1996; pp. 245–252.
8. Oronel, C.; Amaris, C.; Bourouis, M.; Vallès, M. Heat and mass transfer in a bubble plate absorber with NH3 /LiNO3 and NH3 /(LiNO3+ H2O) mixtures. Int. J. Therm. Sci. 2013, 63. [CrossRef]
9. Amaris, C.; Bourouis, M.; Vallès, M. Effect of advanced surfaces on the ammonia absorption process with NH3 /LiNO3 in a tubular bubble absorber. Int. J. Heat Mass Transf. 2014, 72. [CrossRef]
10. Amaris, C.; Bourouis, M.; Vallès, M. Passive intensification of the ammonia absorption process with NH3/LiNO3using carbon nanotubes and advanced surfaces in a tubular bubble absorber. Energy 2014, 68, 519–528. [CrossRef]
11. Kang, Y.T.; Akisawa, A.; Kashiwagi, T. Analytical investigation of two different absorption modes: Falling film and bubble types. Int. J. Refrig. 2000, 23, 430–443. [CrossRef]
12. Castro, J.; Oliet, C.; Rodríguez, I.; Oliva, A. Comparison of the performance of falling film and bubble absorbers for air-cooled absorption systems. Int. J. Therm. Sci. 2009, 48, 1355–1366. [CrossRef]
13. Infante Ferreira, C.A. Combined momentum, heat and mass transfer in vertical slug flow absorbers. Int. J. Refrig. 1985, 8, 326–334. [CrossRef]
14. Cerezo, J.; Best, R.; Romero, R.J. A study of a bubble absorber using a plate heat exchanger with NH3–H2O, NH3–LiNO3 and NH3–NaSCN. Appl. Therm. Eng. 2011, 31, 1869–1876. [CrossRef]
15. Herbine, G.S.; Perez-Blanco, H. Model of an ammonia-water bubble absorber. ASHRAE Trans. 1995, 101, 1324–1334.
16. Fernández-Seara, J.; Sieres, J.; Rodríguez, C.; Vázquez, M. Ammonia–water absorption in vertical tubular absorbers. Int. J. Therm. Sci. 2005, 44, 277–288. [CrossRef]
17. Fernández-Seara, J.; Uhía, F.J.; Sieres, J. Analysis of an air cooled ammonia–water vertical tubular absorber. Int. J. Therm. Sci. 2007, 46, 93–103. [CrossRef]
18. Kang, Y.T.; Christensen, R.N.; Kashiwagi, T. Ammonia-Water bubble absorber with a plate heat exchanger. Int. J. Refrig. 1998, 104, 956–966.
19. Lee, J.-C.; Lee, K.-B.; Chun, B.-H.; Lee, C.H.; Ha, J.J.; Kim, S.H. A study on numerical simulations and experiments for mass transfer in bubble mode absorber of ammonia and water. Int. J. Refrig. 2003, 26, 551–558. [CrossRef]
20. Cerezo, J.; Best, R.; Bourouis, M.; Coronas, A. Comparison of numerical and experimental performance criteria of an ammonia–water bubble absorber using plate heat exchangers. Int. J. Heat Mass Transf. 2010, 53, 3379–3386. [CrossRef]
21. Wang, M.; He, L.; Infante Ferreira, C.A. Ammonia absorption in ionic liquids-based mixtures in plate heat exchangers studied by a semi-empirical heat and mass transfer framework. Int. J. Heat Mass Transf. 2019, 134, 1302–1317. [CrossRef]
22. Sujatha, K.S.; Mani, A.; Srinivasa Murthy, S. Finite element analysis of a bubble absorber. Int. J. Numer. Methods Heat Fluid Flow 1997, 7, 737–750. [CrossRef]
23. Sujatha, K.S.; Mani, A.; Srinivasa, M.S. Analysis of a bubble absorber working with R22 and five organic absorbents. Heat Mass Transf. Stoffuebertragung 1997, 32, 255–259. [CrossRef]
24. Merrill, T.L.; Perez-Blanco, H. Combined heat and mass transfer during bubble absorption in binary solutions. Int. J. Heat Mass Transf. 1997, 40, 589–603. [CrossRef]
25. Terasaka, K.; Oka, J.; Tsuge, H. Ammonia absorption from a bubble expanding at a submerged orifice into water. Chem. Eng. Sci. 2002, 57, 3757–3765. [CrossRef]
26. Kim, J.-K.; Park, C.W.; Kang, Y.T. The effect of micro-scale surface treatment on heat and mass transfer performance for a falling film H2O/LiBr absorber. Int. J. Refrig. 2003, 26, 575–585. [CrossRef]
27. Elperin, T.; Fominykh, A. Four stages of the simultaneous mass and heat transfer during bubble formation and rise in a bubbly absorber. Chem. Eng. Sci. 2003, 58, 3555–3564. [CrossRef]
28. Suresh, M.; Mani, A. Heat and mass transfer studies on R134a bubble absorber in R134a/DMF solution based on phenomenological theory. Int. J. Heat Mass Transf. 2010, 53, 2813–2825. [CrossRef]
29. Staicovici, M.D. A non-Equilibrium phenomenological theory of the mass and heat transfer in physical and chemical interactions: Part II—Modeling of the NH3 /H2O bubble absorption, analytical study of absorption and experiments. Int. J. Heat Mass Transf. 2000, 43, 4175–4188. [CrossRef]
30. Staicovici, M.D. A non-Equilibrium phenomenological theory of the mass and heat transfer in physical and chemical interactions: Part I—Application to NH3 /H2O and other working systems. Int. J. Heat Mass Transf. 2000, 43, 4153–4173. [CrossRef]
31. Kaji, R.; Azzopardi, B.J.; Lucas, D. Investigation of flow development of co-current gas–liquid vertical slug flow. Int. J. Multiph. Flow 2009, 35, 335–348. [CrossRef]
32. Muniz, M.; Sommerfeld, M. On the force competition in bubble columns: A numerical study. Int. J. Multiph. Flow 2020, 128. [CrossRef]
33. Kalogirou, S.A. Artificial neural networks in renewable energy systems applications: A review. Renew. Sustain. Energy Rev. 2000, 5, 373–401. [CrossRef]
34. Mohanraj, M.; Jayaraj, S.; Muraleedharan, C. Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review. Renew. Sustain. Energy Rev. 2012, 16, 1340–1358. [CrossRef]
35. Sözen, A.; Akçayol, M.A. Modelling (using artificial neural-networks) the performance parameters of a solar-driven ejector-absorption cycle. Appl. Energy 2004, 79, 309–325. [CrossRef]
36. Manohar, H.J.; Saravanan, R.; Renganarayanan, S. Modelling of steam fired double effect vapour absorption chiller using neural network. Energy Convers. Manag. 2006, 47, 2202–2210. [CrossRef]
37. Chow, T.T.; Zhang, G.Q.; Lin, Z.; Song, C.L. Global optimization of absorption chiller system by genetic algorithm and neural network. Energy Build. 2002, 34, 103–109. [CrossRef]
38. Hernández, J.A.; Juárez-Romero, D.; Morales, L.I.; Siqueiros, J. COP prediction for the integration of a water purification process in a heat transformer: With and without energy recycling. Desalination 2008, 219, 66–80. [CrossRef]
39. Labus, J.; Bruno, J.C.; Coronas, A. Performance analysis of small capacity absorption chillers by using different modeling methods. Appl. Therm. Eng. 2013, 58, 305–313. [CrossRef]
40. Álvarez, M.E.; Hernández, J.A.; Bourouis, M. Modelling the performance parameters of a horizontal falling film absorber with aqueous (lithium, potassium, sodium) nitrate solution using artificial neural networks. Energy 2016, 102, 313–323. [CrossRef]
41. Amaris, C. Intensification of NH3 Bubble Absorption Process Using Advanced Surfaces and Carbon Nanotubes for NH3 /LiNO3 Absorption Chillers. Ph.D. Thesis, Universitat Rovira i Virgili, Tarragona, Spain, 2013.
42. Libotean, S.; Salavera, D.; Valles, M.; Esteve, X.; Coronas, A. Vapor-liquid equilibrium of ammonia + lithium nitrate + water and ammonia + lithium nitrate solutions from (293.15 to 353.15) K. J. Chem. Eng. Data 2007, 52, 1050–1055. [CrossRef]
43. Libotean, S.; Martín, A.; Salavera, D.; Valles, M.; Esteve, X.; Coronas, A. Densities, viscosities, and heat capacities of ammonia + lithium nitrate and ammonia + lithium nitrate + water solutions between (293.15 and 353.15) K. J. Chem. Eng. Data 2008, 53, 2383–2388. [CrossRef]
44. Cuenca, Y.; Vernet, A.; Vallès, M. Thermal conductivity enhancement of the binary mixture (NH3+ LiNO3) by the addition of CNTs. Int. J. Refrig. 2014, 41, 113–120. [CrossRef]
45. Haltenberger, W. Enthalpy-Concentration charts from vapor pressure data. Ind. Eng. Chem. 1939, 31, 783–786. [CrossRef]
46. McNeely, L.A. Thermodynamic properties of aqueous solutions of lithium bromide. ASHRAE Trans. 1979, 85, 413–434.
47. Infante Ferreira, C.A. Vertical Tubular Absorbers for Ammonia—Salt Absorption Refrigeration. Ph.D. Thesis, Delft University of Technology, Delft, The Netherlands, 1985.
48. Despagne, F. Neural networks in multivariate calibration. Analyst 1998, 123. [CrossRef] [PubMed]
49. Cerezo, J. Estudio Del Proceso De Absorción Con Amoníaco-Agua en Intercambiadores De Placas Para Equipos de Refrigeración Por Absorción. Ph.D. Thesis, Universitat Rovira i Virgili, Tarragona, Spain, 2006.
50. Taylor, B.N.; Kuyatt, C.E. Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, Technical Note 1297; Diane Publishing: Darby, PA, USA, 1994
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spelling Amaris, Carlos2d666509cafda55db0520d6ba6a8cfccAlvarez, Maria E.e18d9ed972c647170b9ac3309c5add06300Bourouis, Mahmouda64d00532f47e110bb6fcc3256abfc61Vallès, Manel0ede95fada4dc34b0ee54daba592c8a13002020-11-12T17:32:16Z2020-11-12T17:32:16Z2020-08-201996-1073https://hdl.handle.net/11323/7275DOI: 10.3390/en13174313Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/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.application/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Energieshttps://www.researchgate.net/publication/343784992_Performance_Assessment_of_an_NH3LiNO3_Bubble_Plate_Absorber_Applying_a_Semi-Empirical_Model_and_Artificial_Neural_NetworksBubble absorptionPlate heat exchangerAdvanced surfacesHeat and mass transfer correlationsSemi-empirical modelArtificial neural networksAmmoniaLithium nitratePerformance assessment of an NH3/LINO3 bubble plate absorber applying a semi-empirical model and artificial neural networksArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1. Amaris, C.; Vallès, M.; Bourouis, M. Vapour absorption enhancement using passive techniques for absorption cooling/heating technologies: A review. Appl. Energy 2018, 231, 826–853. [CrossRef]2. Aggarwal, M.K.; Agarwal, R.S. Thermodynamic properties of lithium nitrate-ammonia mixtures. Int. J. Energy Res. 1986, 10, 59–68. [CrossRef]3. Infante Ferreira, C.A. Thermodynamic and physical property data equations for ammonia-lithium nitrate and ammonia-sodium thiocyanate solutions. Sol. Energy 1984, 32, 231–236. [CrossRef]4. Abdulateef, J.M.; Sopian, K.; Alghoul, M.A. Optimum design for solar absorption refrigeration systems and comparison of the performances using ammonia-water, ammonia-lithium nitrate and ammonia-sodium thiocyanate solutions. Int. J. Mech. Mater. Eng. 2008, 3, 17–24.5. Infante Ferreira, C.A. Operating characteristics of NH3–LiNO3 and NH3–NaSCN absorption refrigeration machines. In Proceedings of the 19th Int. Congr. Refrig, the Hague, The Netherlands, 20–25 August 1995; pp. 321–328.6. Ayala, R.; Frías, J.L.; Lam, L.; Heard, C.L.; Holland, F.A. Experimental assessment of an ammonia/lithium nitrate absorption cooler operated on low temperature geothermal energy. Heat Recover. Syst. CHP 1994, 14, 437–446. [CrossRef]7. Heard, C.L.; Ayala, R.; Best, R. An experimental comparison of an absorption refrigerator using ammonia/water and ammonia/lithium nitrate. In Proceedings of the International Sorption Heat Pump Conference, Montreal, QC, Canada, 17–20 September 1996; pp. 245–252.8. Oronel, C.; Amaris, C.; Bourouis, M.; Vallès, M. Heat and mass transfer in a bubble plate absorber with NH3 /LiNO3 and NH3 /(LiNO3+ H2O) mixtures. Int. J. Therm. Sci. 2013, 63. [CrossRef]9. Amaris, C.; Bourouis, M.; Vallès, M. Effect of advanced surfaces on the ammonia absorption process with NH3 /LiNO3 in a tubular bubble absorber. Int. J. Heat Mass Transf. 2014, 72. [CrossRef]10. Amaris, C.; Bourouis, M.; Vallès, M. Passive intensification of the ammonia absorption process with NH3/LiNO3using carbon nanotubes and advanced surfaces in a tubular bubble absorber. Energy 2014, 68, 519–528. [CrossRef]11. Kang, Y.T.; Akisawa, A.; Kashiwagi, T. Analytical investigation of two different absorption modes: Falling film and bubble types. Int. J. Refrig. 2000, 23, 430–443. [CrossRef]12. Castro, J.; Oliet, C.; Rodríguez, I.; Oliva, A. Comparison of the performance of falling film and bubble absorbers for air-cooled absorption systems. Int. J. Therm. Sci. 2009, 48, 1355–1366. [CrossRef]13. Infante Ferreira, C.A. Combined momentum, heat and mass transfer in vertical slug flow absorbers. Int. J. Refrig. 1985, 8, 326–334. [CrossRef]14. Cerezo, J.; Best, R.; Romero, R.J. A study of a bubble absorber using a plate heat exchanger with NH3–H2O, NH3–LiNO3 and NH3–NaSCN. Appl. Therm. Eng. 2011, 31, 1869–1876. [CrossRef]15. Herbine, G.S.; Perez-Blanco, H. Model of an ammonia-water bubble absorber. ASHRAE Trans. 1995, 101, 1324–1334.16. Fernández-Seara, J.; Sieres, J.; Rodríguez, C.; Vázquez, M. Ammonia–water absorption in vertical tubular absorbers. Int. J. Therm. Sci. 2005, 44, 277–288. [CrossRef]17. Fernández-Seara, J.; Uhía, F.J.; Sieres, J. Analysis of an air cooled ammonia–water vertical tubular absorber. Int. J. Therm. Sci. 2007, 46, 93–103. [CrossRef]18. Kang, Y.T.; Christensen, R.N.; Kashiwagi, T. Ammonia-Water bubble absorber with a plate heat exchanger. Int. J. Refrig. 1998, 104, 956–966.19. Lee, J.-C.; Lee, K.-B.; Chun, B.-H.; Lee, C.H.; Ha, J.J.; Kim, S.H. A study on numerical simulations and experiments for mass transfer in bubble mode absorber of ammonia and water. Int. J. Refrig. 2003, 26, 551–558. [CrossRef]20. Cerezo, J.; Best, R.; Bourouis, M.; Coronas, A. Comparison of numerical and experimental performance criteria of an ammonia–water bubble absorber using plate heat exchangers. Int. J. Heat Mass Transf. 2010, 53, 3379–3386. [CrossRef]21. Wang, M.; He, L.; Infante Ferreira, C.A. Ammonia absorption in ionic liquids-based mixtures in plate heat exchangers studied by a semi-empirical heat and mass transfer framework. Int. J. Heat Mass Transf. 2019, 134, 1302–1317. [CrossRef]22. Sujatha, K.S.; Mani, A.; Srinivasa Murthy, S. Finite element analysis of a bubble absorber. Int. J. Numer. Methods Heat Fluid Flow 1997, 7, 737–750. [CrossRef]23. Sujatha, K.S.; Mani, A.; Srinivasa, M.S. Analysis of a bubble absorber working with R22 and five organic absorbents. Heat Mass Transf. Stoffuebertragung 1997, 32, 255–259. [CrossRef]24. Merrill, T.L.; Perez-Blanco, H. Combined heat and mass transfer during bubble absorption in binary solutions. Int. J. Heat Mass Transf. 1997, 40, 589–603. [CrossRef]25. Terasaka, K.; Oka, J.; Tsuge, H. Ammonia absorption from a bubble expanding at a submerged orifice into water. Chem. Eng. Sci. 2002, 57, 3757–3765. [CrossRef]26. Kim, J.-K.; Park, C.W.; Kang, Y.T. The effect of micro-scale surface treatment on heat and mass transfer performance for a falling film H2O/LiBr absorber. Int. J. Refrig. 2003, 26, 575–585. [CrossRef]27. Elperin, T.; Fominykh, A. Four stages of the simultaneous mass and heat transfer during bubble formation and rise in a bubbly absorber. Chem. Eng. Sci. 2003, 58, 3555–3564. [CrossRef]28. Suresh, M.; Mani, A. Heat and mass transfer studies on R134a bubble absorber in R134a/DMF solution based on phenomenological theory. Int. J. Heat Mass Transf. 2010, 53, 2813–2825. [CrossRef]29. Staicovici, M.D. A non-Equilibrium phenomenological theory of the mass and heat transfer in physical and chemical interactions: Part II—Modeling of the NH3 /H2O bubble absorption, analytical study of absorption and experiments. Int. J. Heat Mass Transf. 2000, 43, 4175–4188. [CrossRef]30. 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Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, Technical Note 1297; Diane Publishing: Darby, PA, USA, 1994CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstream/11323/7275/2/license_rdf42fd4ad1e89814f5e4a476b409eb708cMD52open accessORIGINALPerformance Assessment of an NH3 LiNO3 Bubble.pdfPerformance Assessment of an NH3 LiNO3 Bubble.pdfapplication/pdf2821782https://repositorio.cuc.edu.co/bitstream/11323/7275/1/Performance%20Assessment%20of%20an%20NH3%20LiNO3%20Bubble.pdfa09901daf1ca834e14778078349e5c55MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstream/11323/7275/3/license.txte30e9215131d99561d40d6b0abbe9badMD53open access11323/7275oai:repositorio.cuc.edu.co:11323/72752023-12-14 15:01:43.928CC0 1.0 Universal|||http://creativecommons.org/publicdomain/zero/1.0/open accessRepositorio Universidad de La 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