Multi-phase framework for optimization of thermal and daylight performance of residential buildings based on the combination of ventilation and window design
The environmental design of residential buildings is an arduous process involving a large number of parameters and objectives . Additionally, with the development trend of high-performance housing around the world, its disadvantage - the risk of overheating - has begun to increase, which further sho...
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Published in | Journal of Asian architecture and building engineering Vol. 20; no. 6; pp. 785 - 805 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
02.11.2021
Taylor & Francis Group |
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Abstract | The environmental design of residential buildings is an arduous process involving a large number of parameters and objectives . Additionally, with the development trend of high-performance housing around the world, its disadvantage - the risk of overheating - has begun to increase, which further shows the importance of comprehensive optimization of residential buildings. This study presents a highly targeted optimization framework for residential buildings based on the adjustment of window-related parameters coupled with various natural ventilation patterns. Multiple phases are carried out in this optimization framework to optimizes three objectives, i.e. energy consumption, thermal comfort, daylight environment simultaneously. Phase 1 applies various natural ventilation patterns to explore the improvement potential of ventilation patterns. Phase 2 implements a genetic algorithm to achieve the Pareto optimization of window-related parameters. Phase 3 filters more robust Pareto-optimal based on Multi-Criteria Decision-Making logic to meet the different needs of different skateboards and architectures. The innovation and scientific significance lie in parameters include both the building envelope elements and ventilation patterns, as well as highly targeted for residential building. The results show that natural ventilation effectively improves the potential for simultaneous optimization of multiple objectives, and the optimization framework can adapt to residential buildings with various envelope insulation performance. |
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AbstractList | The environmental design of residential buildings is an arduous process involving a large number of parameters and objectives . Additionally, with the development trend of high-performance housing around the world, its disadvantage – the risk of overheating – has begun to increase, which further shows the importance of comprehensive optimization of residential buildings. This study presents a highly targeted optimization framework for residential buildings based on the adjustment of window-related parameters coupled with various natural ventilation patterns. Multiple phases are carried out in this optimization framework to optimizes three objectives, i.e. energy consumption, thermal comfort, daylight environment simultaneously. Phase 1 applies various natural ventilation patterns to explore the improvement potential of ventilation patterns. Phase 2 implements a genetic algorithm to achieve the Pareto optimization of window-related parameters. Phase 3 filters more robust Pareto-optimal based on Multi-Criteria Decision-Making logic to meet the different needs of different skateboards and architectures. The innovation and scientific significance lie in parameters include both the building envelope elements and ventilation patterns, as well as highly targeted for residential building. The results show that natural ventilation effectively improves the potential for simultaneous optimization of multiple objectives, and the optimization framework can adapt to residential buildings with various envelope insulation performance. |
Author | Cheng, Yanmeng Yagi, Shigekazu Saito, Koichiro Mae, Masayuki Taniguchi, Keiichiro Wang, Jiahe |
Author_xml | – sequence: 1 givenname: Jiahe surname: Wang fullname: Wang, Jiahe email: wang.jiahe@maelab.arch.t.u-tokyo.ac.jp organization: The University of Tokyo – sequence: 2 givenname: Masayuki surname: Mae fullname: Mae, Masayuki organization: The University of Tokyo – sequence: 3 givenname: Keiichiro surname: Taniguchi fullname: Taniguchi, Keiichiro organization: The University of Tokyo – sequence: 4 givenname: Yanmeng surname: Cheng fullname: Cheng, Yanmeng organization: The University of Tokyo – sequence: 5 givenname: Shigekazu surname: Yagi fullname: Yagi, Shigekazu organization: YKK AP Inc – sequence: 6 givenname: Koichiro surname: Saito fullname: Saito, Koichiro organization: YKK AP Inc |
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SubjectTerms | energy efficiency multi-objective optimization natural ventilation Residential building thermal comfort |
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Title | Multi-phase framework for optimization of thermal and daylight performance of residential buildings based on the combination of ventilation and window design |
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