Design optimization of urban typologies: A framework for evaluating building energy performance and outdoor thermal comfort
Sustainable Cities and Society, ISSN: 2210-6707, Vol: 76, Page: 103515
2022
- 50Citations
- 161Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
In the physics-based simulation of urban geometries, the outdoor environment was usually simulated separately from buildings – until recently, when the holistic assessment of the urban environment began to attract more attention. Although analyzing design alternatives with multiple objectives is still a challenge, computational tools enable generating thousands of scenarios to rapidly assess performance corresponding to a specific goal. In this study, we developed a multi-phase optimization framework for conceptual urban design. We tested this framework for urban typologies in Syracuse. The energy performance of each alternative was compared with a baseline. The alternatives that generate wasteful energy performance were filtered out first, then remaining scenarios that performed better than the baseline were analyzed using outdoor thermal comfort autonomy (OTCA). Mid-rise multifamily buildings showed the best performance (55.8% energy improvement compared to the baseline). Although hot week outdoor comfort satisfaction among selected mid-rise typologies was high (92.9–98.5%), the satisfaction in cold week was very low (between 8.4–11.6%) among them. This framework contributes to identifying an acceptable range of design solutions by broadening the perspective of the field toward using a more customized optimization framework in early design that will further guarantee the requirements of energy efficient and sustainable cities.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2210670721007812; http://dx.doi.org/10.1016/j.scs.2021.103515; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85119081329&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2210670721007812; https://dx.doi.org/10.1016/j.scs.2021.103515
Elsevier BV
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