Hybrid Revit and a new MCDM approach of energy effective nursing-home designed by natural stone and green insulation materials
Abstract
The requisition for maintainable constructions has been greatly raising over the last several years. To fulfil the maintainability necessities of a construction, decisions or changes must be done to a construction in the course of the preconstruction and design steps. This can be plausible utilizing building information modelling. To indicate the utilize of building information modelling in maintainable planning, an example nursing-house is received for modelling research. The energy efficiency of nursing-home is analysed utilizing Autodesk Revit and Green Building Studio simulation which contained different characteristics such as annual heating and cooling loads, annual energy usage. Through using the utilize of different building, insulation and roof materials in the nursing-home modelling, the nursing-home modelling is changed into a greener construction modelling. In addition, the effects of using green walls on the facade of the building on the energy performance were analysed. Utilizing simulation, the utilize of non-natural sources can be dramatically decreased through substituting for them with the utilize of sustainable natural sources by that means energy saving. Building information modelling has substantiated to be effective in providing maintainability with alternative material’s assessment and earlier decision-making. Furthermore, this study employed an integrated new MCDM model to evaluate the performance of four natural stones for utilize in a nursing home setting.
Keyword : building performance analysis, building information modelling, energy efficiency, green building, building envelope, energy saving, AROMAN-M
How to Cite
Balo, F., Ulutaş, A., Stević, Željko, Boydak, H., & Zavadskas, E. K. (2025). Hybrid Revit and a new MCDM approach of energy effective nursing-home designed by natural stone and green insulation materials. Journal of Civil Engineering and Management, 31(4), 318–337. https://doi.org/10.3846/jcem.2025.23486
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Clarke, J. (2007). Energy simulation in building design. Routledge. https://doi.org/10.4324/9780080505640
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Dhopte, S., & Daga, A. (2022). Exploring the journey of BIM in the Indian AECO industry (2008–2022) an Excelize perspective. CSI Transactions on ICT, 10(2), 159–174. https://doi.org/10.1007/s40012-022-00364-9
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Hire, S., Sandbhor, S., & Ruikar, K. (2022). Bibliometric survey for adoption of building information modeling (BIM) in construction industry – a safety perspective. Archives of Computational Methods in Engineering, 29(1), 679–693. https://doi.org/10.1007/s11831-021-09584-9
Huskanović, E., Stević, Ž., & Simić, S. (2023). Objective-subjective CRITIC-MARCOS model for selection forklift in internal transport technology processes. Mechatronics and Intelligent Transportation Systems, 2(1), 20–31. https://doi.org/10.56578/mits020103
Jadhav, S., & Ghadge, A. N. (2016). Application of Building information modeling in construction projects: A critical review. International Journal of Engineering Research, 5(1), 26–31.
Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57
Krygiel, E., & Nies, B. (2008). Green BIM: successful sustainable design with building information modeling. John Wiley & Sons.
Kumar, B. (2022). Building information modeling ecosystem: an overview. In Research companion to building information modeling (Chapter 8, pp. 150–167). Edward Elgar Publishing. https://doi.org/10.4337/9781839105524.00016
Kumar, J. V., & Mukherjee, M. (2009). Scope of building information modeling (BIM) in India. Journal of Engineering Science and Technology Review, 2(1), 165–169. https://doi.org/10.25103/jestr.021.30
Li, Y., Chen, X., Wang, X., Xu, Y., & Chen, P. H. (2017). A review of studies on green building assessment methods by comparative analysis. Energy and Buildings, 146, 152–159. https://doi.org/10.1016/j.enbuild.2017.04.076
Meganathan, S., & Nandhini, N. (2018). A review on challenges involved in implementing building information modeling in construction industry. International Research Journal of Engineering and Technology, 5(1), 1329–1331.
Moakher, P. E., & Pimplikar, S. S. (2012). Building information modeling (BIM) and sustainability – using design technology in energy efficient modeling. IOSR Journal of Mechanical and Civil Engineering, 1(2), 10–21. https://doi.org/10.9790/1684-0121021
Mostafavi, N., Farzinmoghadam, M., & Hoque, S. (2015). Envelope retrofit analysis using eQUEST, IESVE Revit Plug-in and Green Building Studio: a university dormitory case study. International Journal of Sustainable Energy, 34(9), 594–613. https://doi.org/10.1080/14786451.2013.848207
Motawa, I., & Carter, K. (2013). Sustainable BIM-based evaluation of buildings. Procedia - Social and Behavioral Sciences, 74, 419–428. https://doi.org/10.1016/j.sbspro.2013.03.015
Nalawade, S., Ramani, H., Gaikwad, R., Pawar, P., & Sathe, P. (2019). Review of BIM technology in construction sector. International Journal of Research and Analytical Reviews, 6(1), 1–3.
Olawumi, T. O., Chan, D. W., Wong, J. K., & Chan, A. P. (2018). Barriers to the integration of BIM and sustainability practices in construction projects: A Delphi survey of international experts. Journal of Building Engineering, 20, 60–71. https://doi.org/10.1016/j.jobe.2018.06.017
Pajić, V., Andrejić, M., & Poledica, M. (2024). A novel approach based on CRITIC-MOOSRA methods for evaluation and selection of cold chain monitoring devices. Journal of Intelligent Management Decision, 3(2), 68–76. https://doi.org/10.56578/jimd030201
Pala, O. (2024). Assessment of the social progress on European Union by logarithmic decomposition of criteria importance. Expert Systems with Applications, 238, Article 121846. https://doi.org/10.1016/j.eswa.2023.121846
Puška, A., Hodžić, I., & Štilić, A. (2023a). Evaluating the knowledge economies within the European Union: A global knowledge index ranking via Entropy and CRADIS methodologies. International Journal of Knowledge and Innovation Studies, 1(2), 103–115. https://doi.org/10.56578/ijkis010203
Puška, A., Stojanović, I., & Štilić, A. (2023b). The influence of objective weight determination methods on electric vehicle selection in urban logistics. Journal of Intelligent Management Decision, 2(3), 117–129. https://doi.org/10.56578/jimd020302
Puška, A., Hodžić, I., Štilić, A., & Murtič, S. (2024). Evaluating European Union countries on climate change management: A fuzzy MABAC approach to the climate change performance index. Journal of Green Economy and Low-Carbon Development, 3(1), 15–25. https://doi.org/10.56578/jgelcd030102
Rahimikhoob, A., Behbahani, S., & Nazarifar, M. H. (2008). Estimation of cooling degree days (CDDs) from AVHRR data and an MLF neural network. Canadian Journal of Remote Sensing, 34(6), 596–600. https://doi.org/10.5589/m08-067
Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: An overview. Energy and Buildings, 42(10), 1592–1600. https://doi.org/10.1016/j.enbuild.2010.05.007
Roshan, G. R., Ghanghermeh, A. A., & Attia, S. (2017). Determining new threshold temperatures for cooling and heating degree day index of different climatic zones of Iran. Renewable Energy, 101, 156–167. https://doi.org/10.1016/j.renene.2016.08.053
Sałabun, W., & Urbaniak, K. (2020). A new coefficient of rankings similarity in decision-making problems. In V. Krzhizhanovskaya, V., Závodszky, G., Lees, M. H., Dongarra, J. J., Sloot, P. M. A., Brissos, S., & Teixeira, J. (Eds.), Lecture notes in computer science: Vol. 12138. Computational science – ICCS 2020 (pp. 632–645). Springer, Cham. https://doi.org/10.1007/978-3-030-50417-5_47
Salvi, S. A., Patil, M. A., Mhetre, M. S., Patil, M. Y., & Shinde, M. A. (2022). Review: Lifecycle assessment of a building by using BIM. International Journal for Research in Applied Science and Engineering Technology, 10, 699–704. https://doi.org/10.22214/ijraset.2022.39901
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