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Development of an integrated approach for the inverse design of built environment by a fast fluid dynamics-based generic algorithm
Dalian Univ Technol, Sch Civil Engn, Dalian 116024, Peoples R China..
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Sustainable Buildings.ORCID iD: 0000-0003-1285-2334
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Sustainable Buildings. Uponor AB, Hackstavagen 1, S-72132 Vasteras, Sweden..ORCID iD: 0000-0001-6266-8485
Beijing Aerosp Inst Metrol & Measurement Technol, Beijing 10000, Peoples R China..
2019 (English)In: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 160, article id 106205Article in journal (Refereed) Published
Abstract [en]

It is essential to further design built environments with improved thermal comfort level, air quality, and reduced energy consumption of the HVAC system. The CFD-based GA was able to identify the global optimal design, but this method requires numbers of CFD simulations which is time consuming. Besides, there is no general rule in determining the critical parameters of GA, such as population size, mutation rate, and crossover rate. Therefore, this study adopted the FFD instead of CFD and developed the FFD-based GA in OpenFOAM. By testing the FFD-based GA in designing the thermal environment in an office with displacement ventilation, it was found that the FFD-based GA had the similar performance with that of the CFD-based GA and saved more than 75% computational effect. Making use of the efficiency of the FFD-based GA, this investigation tested the effect of population size, mutation rate, and crossover rate on the inverse design by GA. In the same design case, the appropriate population size was and mutation rate was m = 0.1, while the crossover rate had no general effect on the inverse design.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 160, article id 106205
Keywords [en]
Population size, Mutation rate, Crossover rate, Optimal design
National Category
Building Technologies
Identifiers
URN: urn:nbn:se:kth:diva-255363DOI: 10.1016/j.buildenv.2019.106205ISI: 000474204100019Scopus ID: 2-s2.0-85067419693OAI: oai:DiVA.org:kth-255363DiVA, id: diva2:1340795
Note

QC 20190806

Available from: 2019-08-06 Created: 2019-08-06 Last updated: 2019-08-06Bibliographically approved

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Liu, WeiWang, Qian

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