Investigation of the parameters affecting the building cooling capacity using the response surface method (RSM)

Year 2022, Volume: 12 Issue: 1, 309 - 319, 15.01.2022

Kadir Özbek Ömer Özyurt

https://doi.org/10.17714/gumusfenbil.972620

Abstract

In this study, the effects of the exterior wall insulation thickness, glass feature and design temperature on the cooling capacity of the building were investigated mathematically and statistically by using an energy analysis program for a sample building in Ankara climate conditions. With these changed parameters, annual cooling loads were calculated and a mathematical model was created. Analyzes were simulated using the hourly analysis program (Carrier HAP) offered by the Carrier company. The importance of the created model was examined by performing analysis of variance (ANOVA) and the p-value was less than 0.05. This shows that the model is reliable. The model was validated and the error rate was found to vary between -0.27 and 0.26. It has been concluded that the minimum cooling capacity for the sample structure will be obtained if the wall heat transmission coefficient varies between 0.46 and 1.03, and the glass heat transmission coefficient varies between 2.48 and 3.7.

Keywords

Carrier HAP, Cooling capacity, Insulation thickness, Response Surface Method (RSM)

Bina soğutma kapasitesine etki eden parametrelerin yanıt yüzey yöntemi (YYY) kullanılarak incelenmesi

Abstract

Bu çalışmada Ankara iklim şartlarında yer alan örnek bir yapı için enerji analiz programı kullanılarak, binanın dış duvar yalıtım kalınlığının, cam özelliğinin ve tasarım sıcaklığının binanın soğutma kapasitesi üzerindeki etkileri matematiksel ve istatistiksel olarak incelenmiştir. Değiştirilen bu parametreler ile yıllık soğutma yükleri hesaplanmış ve matematiksel bir model oluşturulmuştur. Analizler Carrier firması tarafından sunulan saatlik analiz programı (Carrier HAP) kullanılarak simüle edilmiştir. Oluşturulan modelin önemi varyans analizi (ANOVA) yapılarak incelenmiştir ve P-değeri 0.05’ten az çıkmıştır. Bu da modelin güvenilir olduğunu göstermektedir. Modelin doğrulaması yapılmış olup, hata oranı-0.27 ile 0.26 arasında değiştiği görülmüştür. Örnek yapı için minimum soğutma kapasitesinin, duvar ısı iletim katsayısının 0.46 ile 1.03 arasında değiştiği, cam ısı iletim katsayısının ise 2.48 ile 3.7 arasında değiştiği durumda elde edileceği sonucuna ulaşılmıştır.

Keywords

Carrier HAP, Soğutma kapasitesi, Yalıtım kalınlığı, Yanıt Yüzey Yöntemi (YYY)

References

• Alaidroos, A. and Krarti, M. (2015). Optimal design of residential building envelope systems in the Kingdom of Saudi Arabia. Energy and Buildings, 86, 104–117. https://doi.org/10.1016/j.enbuild.2014.09.083
• Aldawi, F., Alam, F., Date, A., Alghamdi, M. and Aldhawi, F. (2013). A new house wall system for residential buildings. Energy and Buildings, 67, 403–418. https://doi.org/10.1016/j.enbuild.2013.08.019
• Atalay, D. (2018). Avrupa ve Amerikan standartlarına göre bina konfor havalandırması sistemlerinde kullanıcılara sağlanması gereken taze hava miktarlarının karşılaştırılması. TTMD Dergisi, 115.
• Bichiou, Y. and Krarti, M. (2011). Optimization of envelope and HVAC systems selection for residential buildings. Energy and Buildings, 43(12), 3373–3382. https://doi.org/10.1016/j.enbuild.2011.08.031
• Binalarda enerji performansı yönetmeliği. (2008). T.C. Resmî Gazete (27075, 5 Aralık 2008)
• Box, G. E. P. and Wilson, K. B. (1951). On the Experimental Attainment of Optimum Conditions. Journal of the Royal Statistical Society: Series B (Methodological), 13(1), 1–38. https://doi.org/10.1111/j.2517-6161.1951.tb00067.x
• Cao, Y. and Shen, D. (2019). Contribution of shared bikes to carbon dioxide emission reduction and the economy in Beijing. Sustainable Cities and Society, 51. https://doi.org/10.1016/j.scs.2019.101749 Carrier Corporation. (2015). Hourly Analysis Program Quick Reference Guide.
• Dabaieh, M., Wanas, O., Hegazy, M. A. and Johansson, E. (2015). Reducing cooling demands in a hot dry climate: A simulation study for non-insulated passive cool roof thermal performance in residential buildings. Energy and Buildings, 89, 142–152. https://doi.org/10.1016/j.enbuild.2014.12.034
• Enerji verimliliği kanunu. (2007). T.C. Resmî Gazete (26510, 18 Nisan 2007)
• Eskin, N. and Türkmen, H. (2008). Analysis of annual heating and cooling energy requirements for office buildings in different climates in Turkey. Energy and Buildings, 40(5), 763–773. https://doi.org/10.1016/j.enbuild.2007.05.008
• Florides, G. A., Tassou, S. A., Kalogirou, S. A. and Wrobel, L. C. (2002). Measures used to lower building energy consumption and their cost effectiveness. Applied Energy, 73(3–4), 299–328. https://doi.org/10.1016/S0306-2619(02)00119-8
• Gelis, K. and Akyurek, E. F. (2021). Entropy generation of different panel radiator types: design of experiments using response surface methodology (RSM). Journal of Building Engineering, 41, 102369. https://doi.org/10.1016/j.jobe.2021.102369
• Geliş, K. ve Yeşildal, F. (2020). Klasik ve modern yapı elemanları kullanılması durumunda ısı iletim katsayısının değişimi ile minimum yalıtım kalınlığının tayini. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 10, 869–877. https://doi.org/10.17714/gumusfenbil.725909
• Giovanardi, A., Troi, A., Sparber, W. and Baggio, P. (2008). Dynamic simulation of a passive house in different locations in Italy. 25th Conference on Passive and Low Energy Architecture(PLEA) (pp. 1–5). Dublin.
• Gunst, R. F., Myers, R. H. and Montgomery, D. C. (1996). Response surface methodology: process and product optimization using designed experiments. Technometrics, 38(3), 285. https://doi.org/10.2307/1270613
• Han, H. Z., Li, B. X., Wu, H. and Shao, W. (2015). Multi-objective shape optimization of double pipe heat exchanger with inner corrugated tube using RSM method. International Journal of Thermal Sciences, 90, 173–186. https://doi.org/10.1016/j.ijthermalsci.2014.12.010
• Huang, J., Hanford, J. and Yang, F. (1999). Residential heating and cooling loads component analysis. Lawrence Berkeley National Laboratory, 44636.
• IEA. (2018). The future of cooling: opportunities for energy-efficient air conditioning. ın the future of cooling: opportunities for energy-efficient air conditioning. Erişim adresi www.iea.org/t&c/
• Kaushik, A., Arif, M., Tumula, P. and Ebohon, O. J. (2020). Effect of thermal comfort on occupant productivity in office buildings: response surface analysis. Building and Environment, 180, 107021. https://doi.org/10.1016/j.buildenv.2020.107021
• Kharseh, M. and Al-Khawaja, M. (2016). Retrofitting measures for reducing buildings cooling requirements in cooling-dominated environment: residential house. Applied Thermal Engineering, 98, 352–356. https://doi.org/10.1016/j.applthermaleng.2015.12.063
• Kim, D. D. and Suh, H. S. (2021). Heating and cooling energy consumption prediction model for high-rise apartment buildings considering design parameters. Energy for Sustainable Development, 61, 1–14. https://doi.org/10.1016/j.esd.2021.01.001
• Liu, T. and Lee, W. L. (2019). Using response surface regression method to evaluate the influence of window types on ventilation performance of Hong Kong residential buildings. Building and Environment, 154, 167–181. https://doi.org/10.1016/j.buildenv.2019.02.043
• Liu, Y., Wang, X. jia, Zhou, S. and Chen, H. (2021). Enhancing public building energy efficiency using the response surface method: an optimal design approach. Environmental Impact Assessment Review, 87. https://doi.org/10.1016/j.eiar.2020.106548
• Mao, N., Song, M., Pan, D. and Deng, S. (2018). Comparative studies on using RSM and TOPSIS methods to optimize residential air conditioning systems. Energy, 144, 98–109. https://doi.org/10.1016/j.energy.2017.11.160
• Samruamphianskun, T., Piumsomboon, P. and Chalermsinsuwan, B. (2012). Effect of ring baffle configurations in a circulating fluidized bed riser using CFD simulation and experimental design analysis. Chemical Engineering Journal, 210, 237–251. https://doi.org/10.1016/j.cej.2012.08.079
• Standartds, ASHRAE. (2019). Energy standard for buildings except low-rise residential buildings (ANSI/ASHRAE/IES Standard 90.1-2019). Erişim adresi ASHRAE Online
• Suleiman, B. M. (2011). Estimation of u-value of traditional North African houses. Applied Thermal Engineering, 31(11–12), 1923–1928. https://doi.org/10.1016/j.applthermaleng.2011.02.038
• Vahedi Torshizi, M., Azadbakht, M. and Kashaninejad, M. (2020). Application of response surface method to energy and exergy analyses of the ohmic heating dryer for sour orange juice. Fuel, 278. https://doi.org/10.1016/j.fuel.2020.118261
• Wang, W., Rivard, H. and Zmeureanu, R. (2006). Floor shape optimization for green building design. Advanced Engineering Informatics, 20(4), 363–378. https://doi.org/10.1016/j.aei.2006.07.001
• Wang, W., Zmeureanu, R. and Rivard, H. (2005). Applying multi-objective genetic algorithms in green building design optimization. Building and Environment, 40(11), 1512–1525. https://doi.org/10.1016/j.buildenv.2004.11.017
• Wong, I. and Baldwin, A. N. (2016). Investigating the potential of applying vertical green walls to high-rise residential buildings for energy-saving in sub-tropical region. Building and Environment, Vol. 97, pp. 34–39. https://doi.org/10.1016/j.buildenv.2015.11.028
• Wright, J. A., Loosemore, H. A. and Farmani, R. (2002). Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and Buildings, 34(9), 959–972. https://doi.org/10.1016/S0378-7788(02)00071-3
• Yi, Y. K. and Malkawi, A. M. (2009). Optimizing building form for energy performance based on hierarchical geometry relation. Automation in Construction, 18(6), 825–833. https://doi.org/10.1016/j.autcon.2009.03.006
• Yu, F. and Leng, J. (2020). Multivariable interactions in simulation-based energy-saving glass roof designs. Solar Energy, 201, 760–772. https://doi.org/10.1016/j.solener.2020.02.095