| Author: | Gao, Tianhao |
| Title: | Optimization of air conditioning parameters using CFD-XGB-GA : a case study for Hong Kong public housing modular flat |
| Advisors: | Mui, Kwok Wai Horace (BEEE) Tsang, Tsz Wun Hayley (BEEE) |
| Degree: | M.Eng. |
| Year: | 2024 |
| Subject: | Air conditioning Ventilation Buildings -- Thermal properties Buildings -- Energy conservation Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Building Environment and Energy Engineering |
| Pages: | iii, 38 pages : color illustrations |
| Language: | English |
| Abstract: | As the space where you spend the most time each day, the thermal comfort of your bedroom is essential to your physical and mental health. Especially during the sleep period, because the lack of sleep caused by discomfort will affect the efficiency of work and study. But air conditioning equipment is also an important way of energy consumption, good thermal comfort is often accompanied by a large amount of energy consumption. Therefore, it is necessary to optimize air conditioning parameters for bedroom scenes. Firstly, this paper analyzes the evaluation of thermal comfort and the selection of key parameters. The accuracy of computational fluid dynamics software is confirmed by experimental analysis. Then, the sample of the trained machine learning model is obtained by numerical simulation of 100 sets of parameters, and the thermal comfort of more parameter combinations is predicted by the trained model. The fitness of the child generation of the equipment energy consumption evaluation based on the empirical formula is obtained. A non-dominant solution set is obtained after generations of inheritance and gene mutation. The results show that the design method can greatly reduce the calculation cost, and can guide the setting of indoor air conditioning parameters through the non-dominated solution, so as to achieve sustainable development. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 7752.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.6 MB | Adobe PDF | View/Open |
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