| Autor: |
Somayeh Davoodabadi Farahani, Amir Davoodabadi Farahani |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Ain Shams Engineering Journal, Vol 15, Iss 3, Pp 102591- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2090-4479 |
| DOI: |
10.1016/j.asej.2023.102591 |
| Popis: |
This research aimed to evaluate the amount of produced fresh water (FWP) in a desalination system based on humidification-dehumidification using TRNSYS software. The study was conducted for one year, analyzing the results for five cities in Iran with different climatic conditions. Meteorological data from Meteonorm software were used for the simulation. Different heating sources, including solar energy (SE) and geothermal energy (GE), were considered in the design. The impact of using three types of collectors and the simultaneous use of SE and GE heating sources was investigated. The findings showed that using a flat plate solar collector resulted in the highest FWP in June and July, as well as during certain day time hours with increased solar radiation intensity. Increasing the number of flat plate collectors and their cross-sectional area intensified the FWP about 10.60%–33.16%. When SE and GE were used as heat sources, increasing the mass flow rate of water and air entering the system led to a decrease and increase in FWP, respectively. The highest FWP for Hamedan city was achieved when using GE simultaneously with a compound parabolic collector. Exergy destruction was analyzed for humidification and dehumidification devices, with the maximum observed in the case of Type74. The LSTM deep learning neural network and the Gaussian process (GP) machine learning algorithm were used to approximate the desalination efficiency, with the GP method exhibiting slightly higher accuracy. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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