Document Type : Original Article


Department of Architecture, Bam Branch, Islamic Azad University, Bam, Iran


New designing techniques have been used recently in design phases of buildings to adapt human thermal comfort. Due to wide range of energy consumption within a building, it is impossible to make a proper decision about the impact of different energy efficiency strategies without simulation tools. Architects need to understand the accuracy and precision of simulation software to use them as valuable tools to predict energy consumption. This research aims to investigate the validity of DesignBuilder simulation software by using the actual traditional house in terms of heat gain. In this study, the comparative method was used to determine the differences in heat gain in a traditional courtyard house in Kerman that was simulated using DesignBuilder software and measured experimentally. This study also reveals that the difference between simulation results and empirical measurement is not more than 10%. It can be concluded that DesignBuilder has enough validity to calculate the amount of heat gain in the rooms adjacent to courtyards.


Main Subjects

  1. Aram, M., and Abessi, O., 2020. Optimal design of green buildings using computational fluid dynamics and climate simulation tools. International Journal of Environmental Science and Technology, 17(2), pp.917–932. Doi: 10.1007/s13762-019-02403-6
  2. Stephan, A., Crawford, R.H., and de Myttenaere, K., 2011. Towards a more holistic approach to reducing the energy demand of dwellings. Procedia Engineering, 21, pp.1033–1041. Doi: 10.1016/j.proeng.2011.11.2109
  3. Amani, N., Sabamehr, A., and Palmero Iglesias, L.M., 2022. Review on Energy Efficiency using the Ecotect Simulation Software for Residential Building Sector. Iranian (Iranica) Journal of Energy & Environment, 13(3), pp.284–294. Doi: 10.5829/ijee.2022.13.03.08
  4. Zhan, J., Liu, W., Wu, F., Li, Z., and Wang, C., 2018. Life cycle energy consumption and greenhouse gas emissions of urban residential buildings in Guangzhou city. Journal of Cleaner Production, 194, pp.318–326. Doi: 10.1016/j.jclepro.2018.05.124
  5. Prieto, A., Knaack, U., Klein, T., and Auer, T., 2017. 25 Years of cooling research in office buildings: Review for the integration of cooling strategies into the building façade (1990–2014). Renewable and Sustainable Energy Reviews, 71, pp.89–102. Doi: 10.1016/j.rser.2017.01.012
  6. Gunay, H.B., O’Brien, W., and Beausoleil-Morrison, I., 2016. Implementation and comparison of existing occupant behaviour models in EnergyPlus. Journal of Building Performance Simulation, 9(6), pp.567–588. Doi: 10.1080/19401493.2015.1102969
  7. Crawley, D.B., Lawrie, L.K., Pedersen, C.O., Winkelmann, F.C., Witte, M.J., Strand, R.K., Liesen, R.J., Buhl, W.F., Huang, Y.J., Henninger, R.H., Glazer, J., Fisher, D.E., Shirey, D.B., Griffith, B.T., Ellis, P.G., and Gu, L., 2004. ENERGYPLUS: NEW, CAPABLE, AND LINKED. Journal of Architectural and Planning Research, 21(4), pp.292–302
  8. Clarke, J.., Janak, M., and Ruyssevelt, P., 1998. Assessing the overall performance of advanced glazing systems. Solar Energy, 63(4), pp.231–241. Doi: 10.1016/S0038-092X(98)00034-6
  9. Mateus, N.M., Pinto, A., and Graça, G.C. da, 2014. Validation of EnergyPlus thermal simulation of a double skin naturally and mechanically ventilated test cell. Energy and Buildings, 75, pp.511–522. Doi: 10.1016/j.enbuild.2014.02.043
  10. Dahanayake, K.W.D.K.C., and Chow, C.L., 2017. Studying the potential of energy saving through vertical greenery systems: Using EnergyPlus simulation program. Energy and Buildings, 138, pp.47–59. Doi: 10.1016/j.enbuild.2016.12.002
  11. Kirimtat, A., Koyunbaba, B.K., Chatzikonstantinou, I., and Sariyildiz, S., 2016. Review of simulation modeling for shading devices in buildings. Renewable and Sustainable Energy Reviews, 53, pp.23–49. Doi: 10.1016/j.rser.2015.08.020
  12. Lomas, K.J., Eppel, H., Martin, C.J., and Bloomfield, D.P., 1997. Empirical validation of building energy simulation programs. Energy and Buildings, 26(3), pp.253–275. Doi: 10.1016/S0378-7788(97)00007-8
  13. Polly, B., Kruis, N., and Roberts, D., 2011. Assessing and improving the accuracy of energy analysis for residential buildings. National Renewable Energy Lab.(NREL), Golden, CO (United States)
  14. Bland, B.H., 1992. Conduction in dynamic thermal models: Analytical tests for validation. Building Services Engineering Research and Technology, 13(4), pp.197–208. Doi: 10.1177/014362449201300403
  15. Judkoff, R.D., 1988. Validation of building energy analysis simulation programs at the solar energy research institute. Energy and Buildings, 10(3), pp.221–239. Doi: 10.1016/0378-7788(88)90008-4
  16. 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), pp.763–773. Doi: 10.1016/j.enbuild.2007.05.008
  17. Tayari, N., and Nikpour, M., 2022. Effect of Different Proportions of Courtyard Buildings in Hot-Dry Climate on Energy Consumption (Case Study: Traditional Courtyard Houses of Kerman, Iran). Iranian Journal of Energy and Environment, 13(1), pp.39–45. Doi: 10.5829/IJEE.2022.13.01.05
  18. Mustafaraj, G., Marini, D., Costa, A., and Keane, M., 2014. Model calibration for building energy efficiency simulation. Applied Energy, 130, pp.72–85. Doi: 10.1016/j.apenergy.2014.05.019
  19. Sun, Y., Heo, Y., Xie, H., Tan, M., Wu, J., and Augenbroe, G., 2011. Uncertainty quantification of microclimate variables in building energy simulation. In: 12th International Building Performance Simulation Association Conference, Sydney, Australia
  20. Baharvand, M., Hamdan, M., and Abdul, M.R., 2013. DesignBuilder verification and validation for indoor natural ventilation. Journal of Basic and Applied Scientific Research (JBASR), 3(4), pp.1–8
  21. Tayari, N., and Nikpour, M., 2022. Investigation on Daylight Quality of Central Courtyard’s Adjacent Rooms in Traditional Houses in Hot Dry Region of Iran: A Case Study Yazdanpanah House. Iranian Journal of Energy and Environment, 13(4), pp.320–332. Doi: 10.5829/IJEE.2022.13.04.01
  22. Abdoli Naser, S., Haghparast, F., Singery, M., and Sattari Sarbangholi, H., 2021. Optimization of Thermal Performance of Windows in Intermediate Housing in Cold and Dry Climate of Tabriz. Iranian Journal of Energy and Environment, 12(4), pp.327–336. Doi: 10.5829/IJEE.2021.12.04.06
  23. Pawar, B.S., and Kanade, G.N., 2018. Energy optimization of building using design builder software. International Journal of New Technology and Research, 4(1)
  24. Moussa, R.R., and Moawad, D.R.M., 2020. Investigating the Efficiency of Building Energy Simulation Software on Architectural Design Process. In: Proceedings of the 2020 9th International Conference on Software and Information Engineering (ICSIE). ACM, New York, NY, USA, pp 37–40
  25. Erba, S., Causone, F., and Armani, R., 2017. The effect of weather datasets on building energy simulation outputs. Energy Procedia, 134, pp.545–554. Doi: 10.1016/j.egypro.2017.09.561
  26. D’Oca, S., and Hong, T., 2015. Occupancy schedules learning process through a data mining framework. Energy and Buildings, 88, pp.395–408. Doi: 10.1016/j.enbuild.2014.11.065
  27. Pisello, A.L., Castaldo, V.L., Taylor, J.E., and Cotana, F., 2016. The impact of natural ventilation on building energy requirement at inter-building scale. Energy and Buildings, 127, pp.870–883. Doi: 10.1016/j.enbuild.2016.06.023
  28. Gobakis, K., and Kolokotsa, D., 2017. Coupling building energy simulation software with microclimatic simulation for the evaluation of the impact of urban outdoor conditions on the energy consumption and indoor environmental quality. Energy and Buildings, 157, pp.101–115. Doi: 10.1016/j.enbuild.2017.02.020
  29. Ren, X., Yan, D., and Hong, T., 2015. Data mining of space heating system performance in affordable housing. Building and Environment, 89, pp.1–13. Doi: 10.1016/j.buildenv.2015.02.009
  30. Nikpour, M., Kandar, M.Z., and Mousavi, E., 2013. Empirical validation of simulation software with experimental measurement of self shading room in term of heat gain. World Applied Sciences Journal, 21(8), pp.1200–1206
  31. Jain, S., Creasey, R.R., Himmelspach, J., White, K.P., and Fu, M., 2011. Validation of autodesk ecotecttm accuracy for thermal and daylighting simulations. In: Proceedings of the 2011 Winter Simulation Conference. Citeseer, pp 3388–3399
  32. Fathalian, A., and Kargarsharifabad, H., 2018. Actual validation of energy simulation and investigation of energy management strategies (Case Study: An office building in Semnan, Iran). Case Studies in Thermal Engineering, 12, pp.510–516. Doi: 10.1016/j.csite.2018.06.007
  33. Ahmad, A., Prakash, O., Kumar, A., Mozammil Hasnain, S.M., Verma, P., Zare, A., Dwivedi, G., and Pandey, A., 2022. Dynamic analysis of daylight factor, thermal comfort and energy performance under clear sky conditions for building: An experimental validation. Materials Science for Energy Technologies, 5, pp.52–65. Doi: 10.1016/j.mset.2021.11.003