Multi-objective optimization of desiccant wheel via analytical model and genetic algorithm. (25th June 2023)
- Record Type:
- Journal Article
- Title:
- Multi-objective optimization of desiccant wheel via analytical model and genetic algorithm. (25th June 2023)
- Main Title:
- Multi-objective optimization of desiccant wheel via analytical model and genetic algorithm
- Authors:
- Li, Heng-Yi
Chen, Yu-Ren
Tsai, Ming-Jui
Huang, Tsair-Fuh
Chen, Chun-Liang
Yang, Sheng-Fu - Abstract:
- Highlights: The analytical model of desiccant wheel was proposed for optimization. The Pareto optimal front was obtained with multi-objective optimization method. The final optimal solution was obtained by decision-making method. Further improvements on dehumidification performance and energy consumption. Abstract: The dehumidification performance and energy consumption of desiccant wheel are affected by many design parameters and operating variables. However, there are few researches concerning multi-objective optimization. Therefore, an optimal design framework combining analytical model, multi-objective optimization and decision-making is proposed. The model was based on the overall heat and mass balances, so the objective functions of the desiccant wheel were derived, and the constraints for the equilibrium of the adsorption and desorption were obtained. Then, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to calculate the Pareto optimal front of the two-objective optimization, and the results were analyzed with psychrometric chart. This solution set includes not only the optimum one with the design method of psychrometric charts, but also includes other better solutions. From the Pareto solutions, the final optimal solution was obtained with the technique for order preference by similarity to ideal solution (TOPSIS) based on four criteria. With the final optimal parameters applied to existing example, the further improvements on the outlet processHighlights: The analytical model of desiccant wheel was proposed for optimization. The Pareto optimal front was obtained with multi-objective optimization method. The final optimal solution was obtained by decision-making method. Further improvements on dehumidification performance and energy consumption. Abstract: The dehumidification performance and energy consumption of desiccant wheel are affected by many design parameters and operating variables. However, there are few researches concerning multi-objective optimization. Therefore, an optimal design framework combining analytical model, multi-objective optimization and decision-making is proposed. The model was based on the overall heat and mass balances, so the objective functions of the desiccant wheel were derived, and the constraints for the equilibrium of the adsorption and desorption were obtained. Then, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to calculate the Pareto optimal front of the two-objective optimization, and the results were analyzed with psychrometric chart. This solution set includes not only the optimum one with the design method of psychrometric charts, but also includes other better solutions. From the Pareto solutions, the final optimal solution was obtained with the technique for order preference by similarity to ideal solution (TOPSIS) based on four criteria. With the final optimal parameters applied to existing example, the further improvements on the outlet process air humidity ratio and the dehumidification coefficient of performance were found. … (more)
- Is Part Of:
- Applied thermal engineering. Volume 228(2023)
- Journal:
- Applied thermal engineering
- Issue:
- Volume 228(2023)
- Issue Display:
- Volume 228, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 228
- Issue:
- 2023
- Issue Sort Value:
- 2023-0228-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-06-25
- Subjects:
- Desiccant wheel -- Dehumidification -- Genetic algorithm -- Multi-objective optimization
Heat engineering -- Periodicals
Heating -- Equipment and supplies -- Periodicals
Periodicals
621.40205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13594311 ↗
http://www.elsevier.com/homepage/elecserv.htt ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.applthermaleng.2023.120411 ↗
- Languages:
- English
- ISSNs:
- 1359-4311
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1580.101000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27107.xml