A neural network approach and thermodynamic model of waste energy recovery in a heat transformer in a water purification process
A theoretical comparison of neural network (NnM) and thermodynamic (ThM) models is carried out to estimate on-line the coefficient of performance (COP) in an absorption heat transformer integrated with a water purification process (AHT–WP). The NnM has been computed for16 variables measured by senso...
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Published in | Desalination Vol. 243; no. 1; pp. 273 - 285 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.07.2009
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | A theoretical comparison of neural network (NnM) and thermodynamic (ThM) models is carried out to estimate on-line the coefficient of performance (COP) in an absorption heat transformer integrated with a water purification process (AHT–WP). The NnM has been computed for16 variables measured by sensors (input and output temperatures for each of the four components absorber, generator, evaporator and condenser; input pressure parameters and LiBr + H
2O concentrations). The ThM estimates the COP values with average temperatures of each component of the AHT–WP. This ThM has been designed for steady-state conditions while the NnM has been developed for steady- and unsteady-state conditions. Both models can be used to calculate the COP values on-line; nevertheless, each model has its own advantages and disadvantages in the AHT–WP design and control. The waste heat simulated for the experimental water purification system is lower than 1 kW, while temperature and lithium bromide concentration are invariable in huge systems. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0011-9164 1873-4464 |
DOI: | 10.1016/j.desal.2008.05.015 |