10.1007/s40095-022-00490-9

Optimization of external wall insulation thickness in buildings using response surface methodology

  • Kadir Ozbek*1,
  • Kadir Gelis1,
  • Omer Ozyurt1,
  1. Department of Mechanical Engineering, Faculty of Engineering, Bolu Abant Izzet Baysal University, Bolu, TR

Published in Issue 2022-03-20

How to Cite

Ozbek, K., Gelis, K., & Ozyurt, O. (2022). Optimization of external wall insulation thickness in buildings using response surface methodology. International Journal of Energy and Environmental Engineering, 13(4 (December 2022). https://doi.org/10.1007/s40095-022-00490-9
Crossref
Scopus
Google Scholar
Europe PMC

Abstract

Abstract Buildings account for one-third of the world’s energy consumption. Reducing this consumption is only possible by making buildings more energy efficient. One of the most efficient methods for increasing the energy efficiency of buildings is thermal insulation. Fuel consumption and therefore emission values can be reduced by achieving adequate thermal insulation of buildings. In this study, the optimum insulation thicknesses for cities in the various climatic regions of Turkey were determined using statistical methods. Insulation thickness, thermal conductivity, heating degree-days (HDD), and fuel type were determined as variable parameters, and the optimum insulation thickness and total heating cost for cities in four different climate zones were determined using the response surface method (RSM). The effect ratios for each parameter on total costs were also reviewed and analyzed using the RSM method. Mathematical models have been developed that estimate the total cost of natural gas, coal, and fuel oil based on thermal insulation thickness, thermal conductivity, and heating degree days. With the mathematical models presented in the study, dependent parameters (total heating cost) can be obtained as a function of independent parameters (fuel type, thermal conductivity of insulation material, and HDD). The models provide a calculation of direct costs for different types of fuels and provide a basis for various research. As a result, the optimum insulation thicknesses for İzmir (HDD: 1781), İstanbul (HDD: 2531), Ankara (HDD: 3303), and Erzurum (HDD: 5393) are 0.059 m, 0.066 m, 0.075 m, and 0.080 m, respectively; reductions in annual total costs were found to be 40.7%, 39.7%, 41.9%, and 50.1%, respectively.

Keywords

  • Insulation,
  • Response surface methodology,
  • Climate zones,
  • Regression analysis,
  • Energy efficiency

References

  1. IEA.: Energy Efficiency 2021, (2021). [Online]. Available:
  2. https://webstore.iea.org/download/direct/4259
  3. International Energy Agency.: “IEA,”
  4. Electricity Information
  5. , (2019).
  6. https://www.iea.org/data-and-statistics/data-browser?country=WORLD&fuel=Energy
  7. supply&indicator=TESbySource (Accessed Nov. 26, 2021)
  8. IEA.: “Heating–Analysis IEA, (2021).
  9. https://www.iea.org/reports/heating
  10. (Accessed Nov. 26, 2021).
  11. Berardi (2015) Building energy consumption in US, EU, and BRIC countries (pp. 128-136) https://doi.org/10.1016/J.PROENG.2015.08.411
  12. Cağlayan et al. (2020) A life cycle costing approach to determine the optimum insulation thickness of existing buildings 40(1) (pp. 1-14)
  13. Chandra et al. (2019) Developing a durable thermally insulated roof slab system using bamboo insulation panels 10(4) (pp. 511-522) https://doi.org/10.1007/s40095-019-0308-x
  14. Schünemann et al. (2022) Heat resilience of apartment buildings in Korea and Germany: comparison of building design and climate https://doi.org/10.1007/s40095-022-00476-7
  15. Shaik et al. (2021) Energy savings and carbon emission mitigation prospective of building’s glazing variety, window-to-wall ratio and wall thickness 14(23) https://doi.org/10.3390/en14238020
  16. Kovalnogov and Chamchiyan (2016) Development and research of an intelectual power system for controlling microclimate in buildings 17(2–4) (pp. 261-278) https://doi.org/10.1615/INTERJENERCLEANENV.2016019207
  17. Erlbeck et al. (2020) Impact of aeration and deaeration of switchable vacuum insulations on the overall heat conductivity using different core materials and filling gases 11(4) (pp. 395-404) https://doi.org/10.1007/S40095-020-00356-Y/FIGURES/13
  18. Axaopoulos et al. (2015) Optimal economic thickness of various insulation materials for different orientations of external walls considering the wind characteristics 90(1) (pp. 939-952) https://doi.org/10.1016/J.ENERGY.2015.07.125
  19. Bencheikh and Bederina (2020) Assessing the duality of thermal performance and energy efficiency of residential buildings in hot arid climate of Laghouat, Algeria 11(1) (pp. 143-162) https://doi.org/10.1007/S40095-019-00318-Z/FIGURES/17
  20. Tunçbilek et al. (2020) Thermal performance based optimization of an office wall containing PCM under intermittent cooling operation https://doi.org/10.1016/J.APPLTHERMALENG.2020.115750
  21. Kharseh and Al-Khawaja (2016) Retrofitting measures for reducing buildings cooling requirements in cooling-dominated environment: residential house (pp. 352-356) https://doi.org/10.1016/j.applthermaleng.2015.12.063
  22. Theodosiou and Papadopoulos (2008) The impact of thermal bridges on the energy demand of buildings with double brick wall constructions 40(11) (pp. 2083-2089) https://doi.org/10.1016/J.ENBUILD.2008.06.006
  23. Kurekci (2016) Determination of optimum insulation thickness for building walls by using heating and cooling degree-day values of all Turkey’s provincial centers (pp. 197-213) https://doi.org/10.1016/j.enbuild.2016.03.004
  24. Cengel and Ghajar Afshin (2014) McGraw-Hill Professional
  25. Duffie and Beckman (2013) Wiley https://doi.org/10.1002/9781118671603
  26. López-Ochoa et al. (2020) Energy renovation of residential buildings in cold mediterranean zones using optimized thermal envelope insulation thicknesses: the case of Spain 12(6) https://doi.org/10.3390/SU12062287
  27. Las-Heras-Casas et al. (2021) Energy renovation of residential buildings in hot and temperate mediterranean zones using optimized thermal envelope insulation thicknesses: the case of spain 11(1) (pp. 1-30) https://doi.org/10.3390/app11010370
  28. Kallioglu et al. (2020) Optimum insulation thickness assessment of different insulation materials for mid-latitude steppe and desert climate (BSH) region of India (pp. 4421-4424) https://doi.org/10.1016/j.matpr.2020.10.590
  29. Kallioğlu et al. (2016) Enviromental and economic analysis of optimum heat insulation thickness in energy saving 6(2) (pp. 160-169)
  30. Liu et al. (2015) Determination of optimum insulation thickness of exterior wall with moisture transfer in hot summer and cold winter zone of China (pp. 1008-1015) https://doi.org/10.1016/J.PROENG.2015.09.072
  31. Yuan and Farnham (2017) Optimum insulation thickness for building exterior walls in 32 regions of china to save energy and reduce CO2 emissions” 9(10) https://doi.org/10.3390/SU9101711
  32. Khalid et al. (2020) A study on energy performance and optimum thickness of thermal insulation for building in different climatic regions in Sudan 73(2) (pp. 146-162) https://doi.org/10.37934/arfmts.73.2.146162
  33. Ziapour et al. (2020) Thermoeconomic analysis for determining optimal insulation thickness for new composite prefabricated wall block as an external wall member in buildings https://doi.org/10.1016/J.JOBE.2020.101354
  34. Nyers et al. (2015) Investment-savings method for energy-economic optimization of external wall thermal insulation thickness (pp. 268-274) https://doi.org/10.1016/J.ENBUILD.2014.10.023
  35. Orzechowski and Orzechowski (2018) Optimal thickness of various insulation materials for different temperature conditions and heat sources in terms of economic aspect 41(4) (pp. 377-393) https://doi.org/10.1177/1744259117708733
  36. Dylewski (2019) Optimal thermal insulation thicknesses of external walls based on economic and ecological heating cost 12(18) https://doi.org/10.3390/EN12183415
  37. Kaynakli et al. (2018) Determination of optimum insulation thickness for different insulation applications considering condensation 25(Supplement 1) (pp. 32-42) https://doi.org/10.17559/TV-20160402130509
  38. Rodríguez-Soria et al. (2014) Review of international regulations governing the thermal insulation requirements of residential buildings and the harmonization of envelope energy loss (pp. 78-90) https://doi.org/10.1016/J.RSER.2014.03.009
  39. Kottek et al. (2006) World map of the Köppen-Geiger climate classification updated 15(3) (pp. 259-263) https://doi.org/10.1127/0941-2948/2006/0130
  40. TS825.:“Thermal insulation requirements for buildings,”
  41. Turkish Standarts Institution, Ankara
  42. , (2008).
  43. https://www1.mmo.org.tr/resimler/dosya_ekler/cf3e258fbdf3eb7_ek.pdf
  44. Geiger, R.: Revised new edition by Geiger. In: Köppen-Geiger, R. (ed.) Climate of the Earth. Klett-Perthes (1961)
  45. Yılmaz and Çiçek (2018) Detailed Köppen-Geiger climate regions of Turkey Türkiye’nin 15(1) https://doi.org/10.14687/jhs.v15i1.5040
  46. Dombayci (2009) Degree-days maps of Turkey for various base temperatures 34(11) (pp. 1807-1812) https://doi.org/10.1016/j.energy.2009.07.030
  47. Dosider.: “Fuel Prices,” (2021).
  48. https://www.dosider.org/?p=5&a=2
  49. Ministry of environment urbanism and climate change.: “Construction and Installation Unit Prices 2021,” (2021).
  50. https://yfk.csb.gov.tr/birim-fiyatlar-i-100468
  51. Wong and Baldwin (2016) Investigating the potential of applying vertical green walls to high-rise residential buildings for energy-saving in sub-tropical region (pp. 34-39) https://doi.org/10.1016/j.buildenv.2015.11.028
  52. Kallioğlu et al. (2020) “Empirical modeling between degree days and optimum insulation thickness for external wall” 42(11) (pp. 1314-1334) https://doi.org/10.1080/15567036.2019.1651797
  53. Kim and Suh (2021) Heating and cooling energy consumption prediction model for high-rise apartment buildings considering design parameters (pp. 1-14) https://doi.org/10.1016/j.esd.2021.01.001
  54. Bolattürk (2008) Optimum insulation thicknesses for building walls with respect to cooling and heating degree-hours in the warmest zone of Turkey 43(6) (pp. 1055-1064) https://doi.org/10.1016/J.BUILDENV.2007.02.014
  55. Hasan (1999) Optimizing insulation thickness for buildings using life cycle cost 63(2) (pp. 115-124) https://doi.org/10.1016/S0306-2619(99)00023-9
  56. Anani and Jibril (1988) Role of thermal insulation in passive designs of buildings 5(3) (pp. 303-313) https://doi.org/10.1016/0741-983X(88)90030-6
  57. Central Bank of the Turkish Republic.: “Inflation and interest rates 2021,” (2021).
  58. https://www.tcmb.gov.tr/wps/wcm/connect/TR/TCMB+TR/Main+Menu/Temel+Faaliyetler/Para+Politikasi/Merkez+Bankasi+Faiz+Oranlari/
  59. .
  60. Hasanzadeh et al. (2019) “Thermal conductivity of low-density polyethylene foams part II: deep investigation using response surface methodology 29(1) (pp. 159-168) https://doi.org/10.1007/S11630-019-1240-3
  61. Sekhar (2021) Process optimization and characterization of manila tamarind seed oil extracted by the soxhlet method 22(1) (pp. 31-52) https://doi.org/10.1615/INTERJENERCLEANENV.2020034890
  62. Kazemian et al. (2021) Performance prediction and optimization of a photovoltaic thermal system integrated with phase change material using response surface method https://doi.org/10.1016/j.jclepro.2020.125748
  63. Mäkelä (2017) Experimental design and response surface methodology in energy applications: a tutorial review (pp. 630-640) https://doi.org/10.1016/J.ENCONMAN.2017.09.021
  64. Zhou (2017) Clear-days operational performance of a hybrid experimental space heating system employing the novel mini-channel solar thermal & PV/T panels and a heat pump (pp. 464-477) https://doi.org/10.1016/J.SOLENER.2017.06.056
  65. Rahimi-Gorji et al. (2015) Statistical optimization of microchannel heat sink (MCHS) geometry cooled by different nanofluids using RSM analysis 130(2) (pp. 1-21) https://doi.org/10.1140/epjp/i2015-15022-8
  66. Zhou et al. (2016) Design of microchannel heat sink with wavy channel and its time-efficient optimization with combined RSM and FVM methods (pp. 715-724) https://doi.org/10.1016/j.ijheatmasstransfer.2016.07.100
  67. Minitab.: “Minitab 19.0 Help,” (2019).
  68. https://support.minitab.com/en-US/minitab/19.1/software-id/128050
  69. Gelis and Akyurek (2021) Entropy generation of different panel radiator types: design of experiments using response surface methodology (RSM) https://doi.org/10.1016/j.jobe.2021.102369