Yes / Models’ accuracy and reliability are important factors for designers of the humidification-dehumidification (HDH) desalination systems. A model used for designing the system must consider all important parameters in order to maintain high accuracy over the wide range of fluctuating conditions. The empirical models for HDH systems which are mostly available in literature are simple and easy to develop but also have limited predictive accuracy for extreme conditions because of consideration of only a few of many influential parameters. Usage of these models may lead to an expensive redesign at latter stages in development of the real system. Therefore, the aim of this paper is to propose the mechanistic model of the HDH desalination process with an improved prediction accuracy as an alternative to conventional models. This model is developed by coupling the heat and mass transfer equations at the water–air interface into enthalpy equations. Performances of the proposed model and an empirical model from literature are compared against experimental data obtained from the HDH system, which is also designed in this work. Results show the proposed model has relatively low mean square error (0.4) hence more accurate than the empirical model with mean square error of 7. It was also found that, the recovery ratio attained by the system increases substantially with an increase of the feed water temperature, but decreases with an increase of water-to-air flow ratio. Freshwater productivity increases with an increasing packing's specific area while doubling of dehumidifiers’ surface area improves the recovery ratio by 16%.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18825 |
| Date | 25 March 2022 |
| Creators | Kaunga, Damson, Patel, Rajnikant, Mujtaba, Iqbal M. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2022 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/), CC-BY-NC-ND |
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