Research Article
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Bioclimatic Façade Design Based on Daylight Parameter and Optimization of Alternatives Through Genetic Algorithms: An Office Building in Ankara

Year 2023, Volume: 7 Issue: 2, 108 - 115, 01.09.2023

Abstract

Today it is clear that, for the mitigation of climate change, built environments should be designed according to energy efficiency criteria. For this reason, environmental conditions must be evalu- ated for site-specific designs based on sustainability. To design energy-efficient structures, it is essential to evaluate the parameters such as sun, wind, and material in the environment and to create alternatives for the orientation of the buildings. In this context, in this article, based on the climatic conditions of Ankara, the facade features of an office building were determined as a result of optimization simulations, and alternatives were created. The environmental condition data of the model, which was designed using the Rhino–Grasshopper program, were obtained with the Ladybug plug-in. Thanks to the Honeybee plug-in, the position of the sun was determined accord- ing to the day and time zones determined in Ankara, and in this way, alternative facades were pro- duced to the facade design at the location of the building. By using the genetic algorithms, the best of these design alternatives was determined. This optimization method was achieved by detecting the highest peak thanks to frontal optimization based on solar radiation with Rhino–Grasshopper's Galapagos plug-in. Results show that the partitions on the facade changed according to the posi- tion of the sun. These partitioning alternatives were processed with Galapagos as different alterna- tive inputs, and as a result, facade partitioning with the best possible alternatives emerged.

References

  • Eiben, A. E., & Smith, J. E. (2015). What is an evolutionary algorithm? In Introduction to evolutionary computing (pp. 25–48). Springer. [CrossRef]
  • Givoni, B. (1992). Comfort, climate analysis, and building design guidelines. Energy and Buildings, 18(1), 11–23. [CrossRef]
  • Goldberg, D. E. (1994). Genetic and evolutionary algorithms come of age. Communications of the ACM, 37(3), 113–119. [CrossRef]
  • Hosseini, S. M., Mohammadi, M., & Guerra-Santin, O. (2019). Interactive kinetic facade: Improving visual comfort based on dynamic daylight and occupant's positions by 2D and 3D shape changes. Building and Environment, 165, 106396. [CrossRef]
  • Knowles, R. L. (2003). The solar envelope: Its meaning for energy and buildings. Energy and Buildings, 35(1), 15–25. [CrossRef]
  • Manzano-Agugliaro, F., Montoya, F. G., Sabio-Ortega, A., & García-Cruz, A.(2015). Review of bioclimatic architecture strategies for achieving thermal comfort. Renewable and Sustainable Energy Reviews, 49, 736–755. [CrossRef]
  • Mirjalili, S. (2019). Evolutionary algorithms and neural networks. Studies in Computational Intelligence, 780.
  • Noble, D., & Kensek, K. (1998). Computer generated solar envelopes in architecture. Journal of Architecture, 3(2), 117–127. [CrossRef]
  • Özerol, G., & Selçuk, S. (2021). Designing facades based on daylight parameter: A proposal for the production of complex surface panelization.
  • URL-1. Retrieved from https ://ww w.lad ybug. tools/ (last access:03.02.2023)
  • URL-2. Retrieved from https://designbuilder.co.uk/cahelp/Content/EnergyPlusWeatherFileFormat. htm (last access:03.02.2023)

Gün Işığı Parametresine Dayalı Biyoklimatik Cephe Tasarımı ve Alternatiflerin Genetik Algoritmalar Aracılığı ile Optimizasyonu: Ankara'da Bir Ofis Binası

Year 2023, Volume: 7 Issue: 2, 108 - 115, 01.09.2023

Abstract

Günümüzde sürdürülebilirlik ilkesine dayanarak yere özgü tasarımlar üretebilmek için çevresel
koşulların değerlendirilmesi gerekmektedir. Enerji performanslarına dayalı yapıların tasarlanabilmesi
için çevredeki güneş, rüzgar, malzeme gibi parametrelerin değerlendirilmesi binaların tasarlanacakları
konumlardaki alternatiflerinin oluşturulmasında fayda sağlamaktadır. Bu bağlamda bu
makalede, Ankara’nın iklim koşullarına dayalı olarak bir ofis yapısının, cephe özelliklerinin optimizasyon
simülasyonları ile alternatiflerinin tasarlanması ve bu tasarım alternatiflerinin genetik algoritmalar
sayesinde değerlendirilmesi ile optimum cephe tasarımının saptanması gerçekleştirilmiştir.
Rhino–Grasshopper programı kullanılarak tasarlanan modelin çevresel koşul verileri Ladybug plugin’i
sayesinde elde edilirken Honeybee plug-in’i aracılığı ile de Ankara’da belirlenen gün ve saat
dilimlerine göre güneşin konumu saptanmış ve yapının bulunduğu konumdaki cephe tasarımına
alternatif cepheler üretilmiştir. Genetik algoritmalar kullanılarak bu alternatif cepheler içinde optimum
cephe modelinin seçilimi gerçekleştirilmiştir. En iyinin seçiminde, Rhino–Grasshopper'ın
Galapagos eklentisi ile güneş ışınımına dayalı ön optimizasyonu yapılmış ve en yüksek tepe noktası
tespit edilmiştir. Sonuçlar, cephedeki bölümlemelerin güneşin konumuna göre değiştiğini göstermektedir.
Cephedeki bölümleme alternatifleri Galapagos ile farklı alternatif girdiler olarak işlenmiş
ve sonuç olarak mümkün olan en iyi alternatiflerle optimum cephe tasarımına ulaşılmıştır.

References

  • Eiben, A. E., & Smith, J. E. (2015). What is an evolutionary algorithm? In Introduction to evolutionary computing (pp. 25–48). Springer. [CrossRef]
  • Givoni, B. (1992). Comfort, climate analysis, and building design guidelines. Energy and Buildings, 18(1), 11–23. [CrossRef]
  • Goldberg, D. E. (1994). Genetic and evolutionary algorithms come of age. Communications of the ACM, 37(3), 113–119. [CrossRef]
  • Hosseini, S. M., Mohammadi, M., & Guerra-Santin, O. (2019). Interactive kinetic facade: Improving visual comfort based on dynamic daylight and occupant's positions by 2D and 3D shape changes. Building and Environment, 165, 106396. [CrossRef]
  • Knowles, R. L. (2003). The solar envelope: Its meaning for energy and buildings. Energy and Buildings, 35(1), 15–25. [CrossRef]
  • Manzano-Agugliaro, F., Montoya, F. G., Sabio-Ortega, A., & García-Cruz, A.(2015). Review of bioclimatic architecture strategies for achieving thermal comfort. Renewable and Sustainable Energy Reviews, 49, 736–755. [CrossRef]
  • Mirjalili, S. (2019). Evolutionary algorithms and neural networks. Studies in Computational Intelligence, 780.
  • Noble, D., & Kensek, K. (1998). Computer generated solar envelopes in architecture. Journal of Architecture, 3(2), 117–127. [CrossRef]
  • Özerol, G., & Selçuk, S. (2021). Designing facades based on daylight parameter: A proposal for the production of complex surface panelization.
  • URL-1. Retrieved from https ://ww w.lad ybug. tools/ (last access:03.02.2023)
  • URL-2. Retrieved from https://designbuilder.co.uk/cahelp/Content/EnergyPlusWeatherFileFormat. htm (last access:03.02.2023)

Details

Primary Language English
Subjects Architectural Design
Journal Section Research Articles
Authors

Gizem ÖZEROL 0000-0003-4000-8536

Semra ARSLAN SELÇUK 0000-0002-2128-2858

Publication Date September 1, 2023
Submission Date June 2, 2022
Published in Issue Year 2023 Volume: 7 Issue: 2

Cite

APA ÖZEROL, G., & ARSLAN SELÇUK, S. (2023). Bioclimatic Façade Design Based on Daylight Parameter and Optimization of Alternatives Through Genetic Algorithms: An Office Building in Ankara. PLANARCH - Design and Planning Research, 7(2), 108-115.

Content of this journal is licensed under a Creative Commons Attribution NonCommercial 4.0 International License

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