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Ampirik Termal Konfor Değerlendirme Yöntemlerinin Bulanık Mantıkla Zenginleştirilmesi

Year 2023, Volume: 8 Issue: 2, 655 - 670, 16.12.2023

Rana Uzun Ferhat Pakdamar

https://doi.org/10.30785/mbud.1320257

Abstract

Yapı kullanıcıları zamanlarının yaklaşık %90'ını iç hava kalitesi, görsel konfor, akustik konfor ve ısıl konfor (diğerlerine göre daha baskın olmak üzere) aradıkları iç mekanlarda geçirmektedirler. Isıl konfor; hava sıcaklığı, hava hızı ve bağıl nem gibi fiziksel parametreler üzerinden incelenmekte ve insanların aktivite seviyesi ve giyim seviyesi de ısıl konforun düzeyinde etkili olmaktadır. ISOEN7730 ve EN15251 gibi ilgili yönetmelikler ve standartlar, konunun profesyonellerce benzer şekilde anlaşılmasını sağlamayı amaçlamaktadır. Bu çalışmalar deneysel yöntemlere dayandığından, bir deneyle desteklenmeyen durumlar için literatürde yer alan sonuçlarda boşluklar vardır. Bu boşluklar "doğru-yanlış" yerine "doğruluk dereceleri" ile değerlendirme yapan Bulanık Mantık Yöntemi ile doldurulabilmektedir. Bu çalışma ile ampirik çalışmalarda yer alan sonuçlardaki boşluklar doldurularak ısıl konforun sağlanması konusundaki bilgi düzeyi artırılabilir ve ileriki çalışmalarla ısıtma-soğutma için harcanan enerjinin çevreye verdiği zarar azaltılabilir.

Keywords

Mimari konfor parametreleri ısıl konfor değerlendirmesi bulanık mantık PMV

References

  • Baran Ergül, D., Varol Malkoçoğlu, A. B., & Acun Özgünler, S. (2022). Mimari Tasarım Karar Verme Süreçlerinde Yapay Zekâ Tabanlı Bulanık Mantık Sistemlerinin Değerlendirilmesi. Mimarlık Bilimleri ve Uygulamaları Dergisi (MBUD), 7(2), 878–899. https://doi.org/10.30785/mbud.1117910
  • Brager, G. S., & de Dear, R. J. (1998). Thermal adaptation in the built environment: a literature review. Energy and Buildings, 27(1), 83–96. https://doi.org/10.1016/S0378-7788(97)00053-4
  • Çekmiş, A. (2016). Fuzzy Logic in Architectural Site Planning Design. Procedia Computer Science, 102, 176–182. https://doi.org/10.1016/J.PROCS.2016.09.386
  • Chen, A., & Chang, V. W. C. (2012). Human health and thermal comfort of office workers in Singapore. Building and Environment, 58, 172–178. https://doi.org/10.1016/J.BUILDENV.2012.07.004
  • Costa, A., Keane, M. M., Torrens, J. I., & Corry, E. (2013). Building operation and energy performance: Monitoring, analysis and optimisation toolkit. Applied Energy, 101, 310–316. https://doi.org/10.1016/J.APENERGY.2011.10.037
  • D’Ambrosio Alfano, F. R., Olesen, B. W., Palella, B. I., & Riccio, G. (2014). Thermal comfort: Design and assessment for energy saving. Energy and Buildings, 81, 326–336. https://doi.org/10.1016/j.enbuild.2014.06.033
  • The MathWorks Inc. (2023). Defuzzification Methods. https://www.mathworks.com/help/fuzzy/defuzzification-methods.html
  • Djongyang, N., Tchinda, R., & Njomo, D. (2010). Thermal comfort: A review paper. Renewable and Sustainable Energy Reviews, 14(9), 2626–2640. https://doi.org/10.1016/J.RSER.2010.07.040
  • Frontczak, M., & Wargocki, P. (2011). Literature survey on how different factors influence human comfort in indoor environments. Building and Environment, 46(4), 922–937. https://doi.org/10.1016/J.BUILDENV.2010.10.021
  • Groarke, L. F. (n.d.). Aristotle: Logic. Internet Encyclopedia of Philosophy and Its Authors. Retrieved September 6, 2023, from https://iep.utm.edu/aristotle- logic/#:~:text=Aristotle%20does%20not%20believe%20that,and%20bad %20forms%20of%20reasoning.
  • Khodakarami, J., & Nasrollahi, N. (2012). Thermal comfort in hospitals – A literature review. Renewable and Sustainable Energy Reviews, 16(6), 4071–4077. https://doi.org/10.1016/J.RSER.2012.03.054
  • Kolokotsa, D. (2007). Artificial intelligence in buildings: A review of the application of fuzzy logic. Advances in Building Energy Research, 1(1), 29–54. https://doi.org/10.1080/17512549.2007.9687268
  • Kolokotsa, D., Tsiavos, D., Stavrakakis, G. S., Kalaitzakis, K., & Antonidakis, E. (2001). Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal±visual comfort and indoor air quality satisfaction.
  • Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259–263. https://doi.org/10.1127/0941-2948/2006/0130
  • Nicol, F. (1993). Thermal Comfort: a handbook for field studies toward an adaptive model. University of East London.
  • Ödük, M. N. (2019). Bulanık Mantık Yöntemi ve Uygulamaları (1st ed.). Iksad Publications. https://iksadyayinevi.com/wp- content/uploads/2020/02/BULANIK-MANTIK-Y%C3%96NTEM%C4%B0- VE-UYGULAMALARI.pdf
  • Olesen, B. W. (2012). Revision of EN 15251: indoor environmental criteria. REHVA Journal, 49(4), 6-12.
  • Olesen, B. W., & Parsons, K. (2002). Introduction to thermal comfort standards and to the proposed new version of EN ISO 7730. Energy and Buildings, 34(6), 537–548. https://doi.org/10.1016/S0378- 7788(02)00004-X
  • Omer, A. M. (2008). Renewable building energy systems and passive human comfort solutions. Renewable and Sustainable Energy Reviews, 12(6), 1562–1587. https://doi.org/10.1016/J.RSER.2006.07.010
  • Ormandy, D., & Ezratty, V. (2012). Health and thermal comfort: From WHO guidance to housing strategies. Energy Policy, 49, 116–121. https://doi.org/10.1016/J.ENPOL.2011.09.003
  • Öz, İ. O., Korcan, S. E., & Bulduk, İ. (2018). Tekstil Sektöründe Termal Konfor Ölçümleri ve Alınacak Önlemlerin Değerlendirilmesi. 2, 21–34. https://dergipark.org.tr/tr/pub/usufedbid/issue/41988/488938
  • Pakdamar, F., & Güler, K. (2012). Evaluation of Flexible Performance of Reinforced Concrete Structures Using a Nonlinear Static Procedure Provided by Fuzzy Logic. Advances in Structural Engineering, 15(12), 2173–2190. https://doi.org/10.1260/1369-4332.15.12.2173
  • Pakdamar, F., & Tuğrul Okbaz, F. (2018). Modeling of feasibility in the context of the environmental effects of high-rise buildings by fuzzy logic. International Refereed Journal Of Architecture and Design, 0(15), 0–0. https://doi.org/10.17365/tmd.2018.3.7
  • Raw, G. J., & Oseland, N. A. (1994). Why another thermal comfort conference? Thermal Comfort: Past, Present and Future, 9–10.
  • Sayigh, A., & Marafia, A. H. (1998). Chapter 1 - Thermal comfort and the development of bioclimatic concept in building design. Renewable and Sustainable Energy Reviews, 2(1–2), 3–24. https://doi.org/10.1016/S1364- 0321(98)00009-4
  • Taleghani, M., Tenpierik, M., Kurvers, S., & Van Den Dobbelsteen, A. (2013). A review into thermal comfort in buildings. Renewable and Sustainable Energy Reviews, 26, 201–215. https://doi.org/10.1016/J.RSER.2013.05.050
  • Wong, N. H. & Khoo, S. S. (2003). Thermal comfort in classrooms in the tropics. Energy and Buildings, 35(4), 337–351. https://doi.org/10.1016/S0378-7788(02)00109-3
  • Yang, L., Yan, H. & Lam, J. C. (2014). Thermal comfort and building energy consumption implications - A review. Applied Energy, 115, 164– 173. https://doi.org/10.1016/J.APENERGY.2013.10.062

Enriching Empirical Thermal Comfort Assessment Methods with Fuzzy Logic

Year 2023, Volume: 8 Issue: 2, 655 - 670, 16.12.2023

Rana Uzun Ferhat Pakdamar

https://doi.org/10.30785/mbud.1320257

Abstract

Building occupants spend approximately 90% of their lives indoors where they want to have indoor air quality, visual, acoustic, and thermal comfort (which is more dominant). Thermal comfort is assessed by physical factors such as operative air temperature, relative humidity, and air velocity. People’s activity level and clothing level are also effective. Related regulations and standards like ISOEN7730 and EN15251 aim to provide a unified understanding of the matter. Since these studies rely on experimental methods, there are instances where certain scenarios lack experimental support, leading to gaps in the results. Those gaps can be filled with the Fuzzy Logic Method, which evaluates with “degrees of truth” instead of “true or false”. With this study, the level of knowledge on providing thermal comfort can be increased by filling the gaps in the empirical studies and the damage caused by heating-cooling energy to the environment can be reduced with further studies.

Keywords

Architectural comfort parameters thermal comfort assessment Fuzzy Logic PMV

References

  • Baran Ergül, D., Varol Malkoçoğlu, A. B., & Acun Özgünler, S. (2022). Mimari Tasarım Karar Verme Süreçlerinde Yapay Zekâ Tabanlı Bulanık Mantık Sistemlerinin Değerlendirilmesi. Mimarlık Bilimleri ve Uygulamaları Dergisi (MBUD), 7(2), 878–899. https://doi.org/10.30785/mbud.1117910
  • Brager, G. S., & de Dear, R. J. (1998). Thermal adaptation in the built environment: a literature review. Energy and Buildings, 27(1), 83–96. https://doi.org/10.1016/S0378-7788(97)00053-4
  • Çekmiş, A. (2016). Fuzzy Logic in Architectural Site Planning Design. Procedia Computer Science, 102, 176–182. https://doi.org/10.1016/J.PROCS.2016.09.386
  • Chen, A., & Chang, V. W. C. (2012). Human health and thermal comfort of office workers in Singapore. Building and Environment, 58, 172–178. https://doi.org/10.1016/J.BUILDENV.2012.07.004
  • Costa, A., Keane, M. M., Torrens, J. I., & Corry, E. (2013). Building operation and energy performance: Monitoring, analysis and optimisation toolkit. Applied Energy, 101, 310–316. https://doi.org/10.1016/J.APENERGY.2011.10.037
  • D’Ambrosio Alfano, F. R., Olesen, B. W., Palella, B. I., & Riccio, G. (2014). Thermal comfort: Design and assessment for energy saving. Energy and Buildings, 81, 326–336. https://doi.org/10.1016/j.enbuild.2014.06.033
  • The MathWorks Inc. (2023). Defuzzification Methods. https://www.mathworks.com/help/fuzzy/defuzzification-methods.html
  • Djongyang, N., Tchinda, R., & Njomo, D. (2010). Thermal comfort: A review paper. Renewable and Sustainable Energy Reviews, 14(9), 2626–2640. https://doi.org/10.1016/J.RSER.2010.07.040
  • Frontczak, M., & Wargocki, P. (2011). Literature survey on how different factors influence human comfort in indoor environments. Building and Environment, 46(4), 922–937. https://doi.org/10.1016/J.BUILDENV.2010.10.021
  • Groarke, L. F. (n.d.). Aristotle: Logic. Internet Encyclopedia of Philosophy and Its Authors. Retrieved September 6, 2023, from https://iep.utm.edu/aristotle- logic/#:~:text=Aristotle%20does%20not%20believe%20that,and%20bad %20forms%20of%20reasoning.
  • Khodakarami, J., & Nasrollahi, N. (2012). Thermal comfort in hospitals – A literature review. Renewable and Sustainable Energy Reviews, 16(6), 4071–4077. https://doi.org/10.1016/J.RSER.2012.03.054
  • Kolokotsa, D. (2007). Artificial intelligence in buildings: A review of the application of fuzzy logic. Advances in Building Energy Research, 1(1), 29–54. https://doi.org/10.1080/17512549.2007.9687268
  • Kolokotsa, D., Tsiavos, D., Stavrakakis, G. S., Kalaitzakis, K., & Antonidakis, E. (2001). Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal±visual comfort and indoor air quality satisfaction.
  • Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259–263. https://doi.org/10.1127/0941-2948/2006/0130
  • Nicol, F. (1993). Thermal Comfort: a handbook for field studies toward an adaptive model. University of East London.
  • Ödük, M. N. (2019). Bulanık Mantık Yöntemi ve Uygulamaları (1st ed.). Iksad Publications. https://iksadyayinevi.com/wp- content/uploads/2020/02/BULANIK-MANTIK-Y%C3%96NTEM%C4%B0- VE-UYGULAMALARI.pdf
  • Olesen, B. W. (2012). Revision of EN 15251: indoor environmental criteria. REHVA Journal, 49(4), 6-12.
  • Olesen, B. W., & Parsons, K. (2002). Introduction to thermal comfort standards and to the proposed new version of EN ISO 7730. Energy and Buildings, 34(6), 537–548. https://doi.org/10.1016/S0378- 7788(02)00004-X
  • Omer, A. M. (2008). Renewable building energy systems and passive human comfort solutions. Renewable and Sustainable Energy Reviews, 12(6), 1562–1587. https://doi.org/10.1016/J.RSER.2006.07.010
  • Ormandy, D., & Ezratty, V. (2012). Health and thermal comfort: From WHO guidance to housing strategies. Energy Policy, 49, 116–121. https://doi.org/10.1016/J.ENPOL.2011.09.003
  • Öz, İ. O., Korcan, S. E., & Bulduk, İ. (2018). Tekstil Sektöründe Termal Konfor Ölçümleri ve Alınacak Önlemlerin Değerlendirilmesi. 2, 21–34. https://dergipark.org.tr/tr/pub/usufedbid/issue/41988/488938
  • Pakdamar, F., & Güler, K. (2012). Evaluation of Flexible Performance of Reinforced Concrete Structures Using a Nonlinear Static Procedure Provided by Fuzzy Logic. Advances in Structural Engineering, 15(12), 2173–2190. https://doi.org/10.1260/1369-4332.15.12.2173
  • Pakdamar, F., & Tuğrul Okbaz, F. (2018). Modeling of feasibility in the context of the environmental effects of high-rise buildings by fuzzy logic. International Refereed Journal Of Architecture and Design, 0(15), 0–0. https://doi.org/10.17365/tmd.2018.3.7
  • Raw, G. J., & Oseland, N. A. (1994). Why another thermal comfort conference? Thermal Comfort: Past, Present and Future, 9–10.
  • Sayigh, A., & Marafia, A. H. (1998). Chapter 1 - Thermal comfort and the development of bioclimatic concept in building design. Renewable and Sustainable Energy Reviews, 2(1–2), 3–24. https://doi.org/10.1016/S1364- 0321(98)00009-4
  • Taleghani, M., Tenpierik, M., Kurvers, S., & Van Den Dobbelsteen, A. (2013). A review into thermal comfort in buildings. Renewable and Sustainable Energy Reviews, 26, 201–215. https://doi.org/10.1016/J.RSER.2013.05.050
  • Wong, N. H. & Khoo, S. S. (2003). Thermal comfort in classrooms in the tropics. Energy and Buildings, 35(4), 337–351. https://doi.org/10.1016/S0378-7788(02)00109-3
  • Yang, L., Yan, H. & Lam, J. C. (2014). Thermal comfort and building energy consumption implications - A review. Applied Energy, 115, 164– 173. https://doi.org/10.1016/J.APENERGY.2013.10.062
There are 28 citations in total.

Details

Primary Language English
Subjects Information Technologies in Architecture and Design, Architecture (Other)
Journal Section Research Articles
Authors

Rana Uzun 0000-0001-9414-0175

Ferhat Pakdamar 0000-0002-5594-3095

Publication Date December 16, 2023
Submission Date July 7, 2023
Published in Issue Year 2023 Volume: 8 Issue: 2

Cite

APA Uzun, R., & Pakdamar, F. (2023). Enriching Empirical Thermal Comfort Assessment Methods with Fuzzy Logic. Journal of Architectural Sciences and Applications, 8(2), 655-670. https://doi.org/10.30785/mbud.1320257
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