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BIM and orthogonal test methods to optimize the energy consumption of green buildings

    Xiaojuan Li Affiliation
    ; Mingchao Lin Affiliation
    ; Ming Jiang Affiliation
    ; C. Y. Jim Affiliation
    ; Ke Liu Affiliation
    ; Huipin Tserng Affiliation

Abstract

The construction industry’s rapid growth significantly impacts energy consumption and environmental health. It is crucial to develop optimization strategies to enhance green building energy efficiency and encompass comprehensive analysis methods. This study aims to introduce and validate a novel framework for optimizing energy efficiency design in green buildings by integrating Building Information Modeling (BIM) technology, Life Cycle Cost (LCC) analysis, and orthogonal testing methods, focusing on enhancing energy efficiency and reducing life cycle costs. The optimization parameters for the building envelope are identified by analyzing energy consumption components and key green building factors. The orthogonal testing method was applied to streamline design options. Building Energy Consumption Simulation (BECS) software and LCC analysis tools were employed to calculate each optimized option’s total annual energy consumption and the current life cycle costs. Using the efficiency coefficient method, each optimization scheme’s energy consumption and economic indicators were thoroughly analyzed. The framework’s validity and applicability were confirmed through an empirical analysis of a campus green building case in Fujian Province, demonstrating that the optimized framework could reduce energy consumption by 4.85 kWh/m2 per year and lower costs by 38.89 Yuan/m2 compared to the reference building. The case study highlights the framework’s significant benefits in enhancing environmental performance and economic gains. The results provide critical parameter selection and offer scientific and technological support for the design of building energy efficiency, promoting optimization techniques and sustainable development within the construction industry.

Keyword : green building, BIM (building information model), economic optimization, energy consumption, energy-saving technology, energy-efficient design

How to Cite
Li, X., Lin, M., Jiang, M., Jim, C. Y., Liu, K., & Tserng, H. (2024). BIM and orthogonal test methods to optimize the energy consumption of green buildings. Journal of Civil Engineering and Management, 30(8), 670–690. https://doi.org/10.3846/jcem.2024.21745
Published in Issue
Sep 17, 2024
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References

Ahmad, T., Thaheem, M. J., & Anwar, A. (2016). Developing a green-building design approach by selective use of systems and techniques. Architectural Engineering and Design Management, 12(1), 29–50. https://doi.org/10.1080/17452007.2015.1095709

Al-Sakkaf, A., Zayed, T., Bagchi, A., Mahmoud, S., & Pickup, D. (2020). Development of a sustainability rating tool for heritage buildings: Future implications. Smart and Sustainable Built Environment, 11(1), 93–109. https://doi.org/10.1108/SASBE-04-2020-0047

Arenas, N. F., & Shafique, M. (2023). Recent progress on BIM-based sustainable buildings: State of the art review. Developments in the Built Environment, 15, Article 100176. https://doi.org/10.1016/j.dibe.2023.100176

Ascione, F., Bianco, N., Mauro, G. M., & Napolitano, D. F. (2019). Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones. Energy, 174, 359–374. https://doi.org/10.1016/j.energy.2019.02.182

Azmi, N. A., & Ibrahim, S. H. (2020). A comprehensive review on thermal performance and envelope thermal design of mosque buildings. Building and Environment, 185, Article 107305. https://doi.org/10.1016/j.buildenv.2020.107305

Baldini, M., Brøgger, M., Jacobsen, H. K., & Wittchen, K. B. (2020). Cost-effectiveness of energy efficiency improvements for a residential building stock in a Danish district heating area. Energy Efficiency, 13, 1737–1761. https://doi.org/10.1007/s12053-020-09889-x

Bracht, M., Melo, A., & Lamberts, R. (2021). A metamodel for building information modeling-building energy modeling integration in early design stage. Automation in Construction, 121, Article 103422. https://doi.org/10.1016/j.autcon.2020.103422

Bui, D.-K., Nguyen, T. N., Ghazlan, A., Ngo, N.-T., & Ngo, T. D. (2020). Enhancing building energy efficiency by adaptive façade: A computational optimization approach. Applied Energy, 265, Article 114797. https://doi.org/10.1016/j.apenergy.2020.114797

Chandhran, K. D., & Elavenil, S. (2023). A comprehensive state-of-the-art review of sustainable thermal insulation system used in external walls for reduction in energy consumption in buildings. International Journal of Green Energy, 20(9), 895–913. https://doi.org/10.1080/15435075.2022.2120769

Chang, Y., Li, X., Masanet, E., Zhang, L., Huang, Z., & Ries, R. (2018). Unlocking the green opportunity for prefabricated buildings and construction in China. Resources, Conservation and Recycling, 139, 259–261. https://doi.org/10.1016/j.resconrec.2018.08.025

Chen, H., & An, Y.-c. (2024). Green residential building design scheme optimization based on the orthogonal experiment EWM-TOPSIS. Buildings, 14(2), Article 452. https://doi.org/10.3390/buildings14020452

Chen, Z., Hammad, A. W., Kamardeen, I., & Akbarnezhad, A. (2020). Optimising embodied energy and thermal performance of thermal insulation in building envelopes via an automated building information modelling (BIM) tool. Buildings, 10(12), Article 218. https://doi.org/10.3390/buildings10120218

Chen, S., Jin, E., Xu, G., Zhuo, S., & Chen, X. (2022a). Factors influencing the low-temperature properties of styrene-butadiene-styrene modified asphalt based on orthogonal tests. Polymers, 15(1), Article 52. https://doi.org/10.3390/polym15010052

Chen, Y., Cai, X., Li, J., Zhang, W., and Liu, Z. (2022b). The values and barriers of Building Information Modeling (BIM) implementation combination evaluation in smart building energy and efficiency. Energy Reports, 8, 96–111. https://doi.org/10.1016/j.egyr.2022.03.075

Chi, D. A., González M, E., Valdivia, R., & Gutiérrez J, E. (2021). Parametric design and comfort optimization of dynamic shading structures. Sustainability, 13(14), Article 7670. https://doi.org/10.3390/su13147670

Deng, J.-X., Li, X., Li, X.-J., & Wei, T.-B. (2023). Analysis of the performance of recycled insulation concrete and optimal mix ratio design based on orthogonal testing. Materials, 16(16), Article 5688. https://doi.org/10.3390/ma16165688

Derazgisou, S., Bausys, R., & Fayaz, R. (2018). Computational optimization of housing complexes forms to enhance energy efficiency. Journal of Civil Engineering and Management, 24(3), 193–205. https://doi.org/10.3846/jcem.2018.1678

Ding, Z., Fan, Z., Tam, V. W., Bian, Y., Li, S., Illankoon, I. C. S., & Moon, S. (2018). Green building evaluation system implementation. Building and Environment, 133, 32–40. https://doi.org/10.1016/j.buildenv.2018.02.012

Dräger, P., & Letmathe, P. (2022). Value losses and environmental impacts in the construction industry–Tradeoffs or correlates?. Journal of Cleaner Production, 336, Article 130435. https://doi.org/10.1016/j.jclepro.2022.130435

Ferrara, M., Fabrizio, E., Virgone, J., & Filippi, M. (2016). Energy systems in cost-optimized design of nearly zero-energy buildings. Automation in Construction, 70, 109–127. https://doi.org/10.1016/j.autcon.2016.06.007

Foroughi, R., Asadi, S., & Khazaeli, S. (2021). On the optimization of energy efficient fenestration for small commercial buildings in the United States. Journal of Cleaner Production, 283, Article 124604. https://doi.org/10.1016/j.jclepro.2020.124604

Franco, A., Miserocchi, L., & Testi, D. (2023). Energy efficiency in shared buildings: Quantification of the potential at multiple scales. Energy Reports, 9, 84–95. https://doi.org/10.1016/j.egyr.2022.11.142

Fujian Academy of Building Science. (2015). Energy conservation engineering practices for civil building envelopes in Fujian Province and data (DBJT13-97). Fujian Provincial Building Standard Design.

Gao, R., Zhang, H., Li, A., Wen, S., Du, W., & Deng, B. (2021). Research on optimization and design methods for air distribution system based on target values. Building Simulation, 14, 721–735. https://doi.org/10.1007/s12273-020-0679-1

Gerbino, S., Cieri, L., Rainieri, C., & Fabbrocino, G. (2021). On BIM interoperability via the IFC standard: An assessment from the structural engineering and design viewpoint. Applied Sciences, 11(23), Article 11430. https://doi.org/10.3390/app112311430

Gondal, I. A., Syed Athar, M., & Khurram, M. (2021). Role of passive design and alternative energy in building energy optimization. Indoor and Built Environment, 30(2), 278–289. https://doi.org/10.1177/1420326X19887486

Guo, K., Li, Q., Zhang, L., & Wu, X. (2021). BIM-based green building evaluation and optimization: A case study. Journal of Cleaner Production, 320, Article 128824. https://doi.org/10.1016/j.jclepro.2021.128824

Hao, J. L., Cheng, B., Lu, W., Xu, J., Wang, J., Bu, W., & Guo, Z. (2020). Carbon emission reduction in prefabrication construction during materialization stage: A BIM-based life-cycle assessment approach. Science of the Total Environment, 723, Article 137870. https://doi.org/10.1016/j.scitotenv.2020.137870

Hong, J., Shen, G. Q., Mao, C., Li, Z., & Li, K. (2016). Life-cycle energy analysis of prefabricated building components: an input–output-based hybrid model. Journal of Cleaner Production, 112, 2198–2207. https://doi.org/10.1016/j.jclepro.2015.10.030

Huo, T., Ren, H., and Cai, W. (2019). Estimating urban residential building-related energy consumption and energy intensity in China based on improved building stock turnover model. Science of the Total Environment, 650, 427–437. https://doi.org/10.1016/j.scitotenv.2018.09.008

Ilbeigi, M., Ghomeishi, M., & Dehghanbanadaki, A. (2020). Prediction and optimization of energy consumption in an office building using artificial neural network and a genetic algorithm. Sustainable Cities and Society, 61, Article 102325. https://doi.org/10.1016/j.scs.2020.102325

Ilhan, B., & Yaman, H. (2016). Green building assessment tool (GBAT) for integrated BIM-based design decisions. Automation in Construction, 70, 26–37. https://doi.org/10.1016/j.autcon.2016.05.001

Illankoon, I. C. S., Tam, V. W., Le, K. N., Tran, C. N., & Ma, M. (2019). Review on green building rating tools worldwide: Recommendations for Australia. Journal of Civil Engineering and Management, 25(8), 831–847. https://doi.org/10.3846/jcem.2019.10928

Ismail, Z.-A. (2021). Maintenance management practices for green building projects: towards hybrid BIM system. Smart and Sustainable Built Environment, 10(4), 616–630. https://doi.org/10.1108/SASBE-03-2019-0029

Jang, J., Han, J., Kim, M.-H., Kim, D.-w., & Leigh, S.-B. (2021). Extracting influential factors for building energy consumption via data mining approaches. Energies, 14(24), Article 8505. https://doi.org/10.3390/en14248505

Javed, N., Thaheem, M. J., Bakhtawar, B., Nasir, A. R., Khan, K. I. A., & Gabriel, H. F. (2019). Managing risk in green building projects: toward a dedicated framework. Smart and Sustainable Built Environment, 9(2), 156–173. https://doi.org/10.1108/SASBE-11-2018-0060

Ji, Y., Lv, J., Li, H. X., Liu, Y., Yao, F., Liu, X., & Wang, S. (2024). Improving the performance of prefabricated houses through multi-objective optimization design. Journal of Building Engineering, 84, Article 108579. https://doi.org/10.1016/j.jobe.2024.108579

Kim, M.-K., Jang, W.-J., Choi, H.-A., & Jun, H.-J. (2011). A study on the application possibility of green building design process based on Building Information Modeling (BIM) for sustainable architecture. KIEAE Journal, 11(2), 113–122.

Kiss, B., & Szalay, Z. (2020). Modular approach to multi-objective environmental optimization of buildings. Automation in Construction, 111, Article 103044. https://doi.org/10.1016/j.autcon.2019.103044

Li, H. X., Li, Y., Jiang, B., Zhang, L., Wu, X., & Lin, J. (2020). Energy performance optimisation of building envelope retrofit through integrated orthogonal arrays with data envelopment analysis. Renewable Energy, 149, 1414–1423. https://doi.org/10.1016/j.renene.2019.10.143

Li, Q., Zhang, L., Zhang, L., & Wu, X. (2021a). Optimizing energy efficiency and thermal comfort in building green retrofit. Energy, 237, Article 121509. https://doi.org/10.1016/j.energy.2021.121509

Li, W., Li, H., & Wang, S. (2021b). An event-driven multi-agent based distributed optimal control strategy for HVAC systems in IoT-enabled smart buildings. Automation in Construction, 132, Article 103919. https://doi.org/10.1016/j.autcon.2021.103919

Li, X.-J., Lai, J.-y., Ma, C.-y., & Wang, C. (2021c). Using BIM to research carbon footprint during the materialization phase of prefabricated concrete buildings: A China study. Journal of Cleaner Production, 279, Article 123454. https://doi.org/10.1016/j.jclepro.2020.123454

Li, Q., Hu, H., Ma, L., Wang, Z., Arıcı, M., Li, D., Luo, D., Jia, J., Jiang, W., & Qi, H. (2022). Evaluation of energy-saving retrofits for sunspace of rural residential buildings based on orthogonal experiment and entropy weight method. Energy for Sustainable Development, 70, 569–580. https://doi.org/10.1016/j.esd.2022.09.007

Li, X., Xie, W., Yang, T., Lin, C., & Jim, C. Y. (2023). Carbon emission evaluation of prefabricated concrete composite plates during the building materialization stage. Building and Environment, 232, Article 110045. https://doi.org/10.1016/j.buildenv.2023.110045

Liu, G., Gu, T., Xu, P., Hong, J., Shrestha, A., & Martek, I. (2019). A production line-based carbon emission assessment model for prefabricated components in China. Journal of Cleaner Production, 209, 30–39. https://doi.org/10.1016/j.jclepro.2018.10.172

Liu, Y., Wang, W., Huang, Y., Song, J., & Zhou, Z. (2024). Energy performance analysis and study of an office building in an extremely hot and cold region. Sustainability, 16(2), Article 572. https://doi.org/10.3390/su16020572

Lu, S., Li, J., & Lin, B. (2020). Reliability analysis of an energy-based form optimization of office buildings under uncertainties in envelope and occupant parameters. Energy and Buildings, 209, Article 109707. https://doi.org/10.1016/j.enbuild.2019.109707

Ma, M., Cai, W., & Wu, Y. (2019). China act on the energy efficiency of civil buildings (2008): A decade review. Science of The Total Environment, 651, 42–60. https://doi.org/10.1016/j.scitotenv.2018.09.118

Ma, S., Li, Z., Li, L., & Yuan, M. (2023). Coupling coordination degree spatiotemporal characteristics and driving factors between new urbanization and construction industry: Evidence from China. Engineering, Construction and Architectural Management, 30(10), 5280–5301. https://doi.org/10.1108/ECAM-05-2022-0471

Meng, X., Yu, W., Zheng, C., Wang, D., & Cao, X. (2019). Path analysis of energy-saving technology in Yangtze River basin based on multi-objective and multi-parameter optimisation. Journal of Thermal Science, 28, 1164–1175. https://doi.org/10.1007/s11630-019-1102-z

Ministry of Construction Engineering Quality and Safety Supervision and Industry Development Division. (2007). National technical measures for design of civil construction. Special edition: Energy conservation (JSCS-D). China Building Standard Design and Research Institute.

Ministry of Housing and Urban-Rural Development. (2006). Value table of financial benchmark rate of return of construction project. China National Development and Reform Commission.

Ministry of Housing and Urban-Rural Development. (2015). The design standard for energy efficiency of public buildings (GB50189-2015).

Ministry of Housing and Urban-Rural Development. (2016). Code for thermal design of civil building (GB50176-2016).

Ministry of Housing and Urban-Rural Development. (2019). Test methods of air permeability, watertightness, wind load resistance performance for building external windows and doors (GB/T 7106-2019).

Misra, A., Singh, H., & Katiyar, A. (2021). A review on coefficient of performance of HVAC framework. International Journal of Research in Engineering, Science and Management, 4(7), 36–39.

Mora, D., Carpino, C., & De Simone, M. (2018). Energy consumption of residential buildings and occupancy profiles. A case study in Mediterranean climatic conditions. Energy Efficiency, 11, 121–145. https://doi.org/10.1007/s12053-017-9553-0

Nagrale, S., & Bais, M. (2020). Energy efficiency analysis and modelling of a green building using Revit software. International Journal of Research in Engineering, Science and Management, 3(3), 365–367.

Norouzi, M., Colclough, S., Jiménez, L., Gavaldà, J., & Boer, D. (2022). Low-energy buildings in combination with grid decarbonization, life cycle assessment of passive house buildings in Northern Ireland. Energy and Buildings, 261, Article 111936. https://doi.org/10.1016/j.enbuild.2022.111936

Peymankar, M., Davari, M., & Ranjbar, M. (2021). Maximizing the expected net present value in a project with uncertain cash flows. European Journal of Operational Research, 294(2), 442–452. https://doi.org/10.1016/j.ejor.2021.01.039

Rached, E., & Anber, M. (2022). Energy retrofitting strategies for office buildings in hot arid climate. International Journal of Low-Carbon Technologies, 17, 506–512. https://doi.org/10.1093/ijlct/ctac031

Rahimian, F. P., Seyedzadeh, S., Oliver, S., Rodriguez, S., & Dawood, N. (2020). On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning. Automation in Construction, 110, Article 103012. https://doi.org/10.1016/j.autcon.2019.103012

Ratajczak, J., Siegele, D., & Niederwieser, E. (2023). Maximizing energy efficiency and daylight performance in office buildings in BIM through RBFOpt model-based optimization: The GENIUS project. Buildings, 13(7), Article 1790. https://doi.org/10.3390/buildings13071790

Ren, Z., Tang, Z., & James, M. (2021). Typical meteorological year weather files for building energy modelling. Australia’s National Science Agency.

Sadeghifam, A. N., Meynagh, M. M., Tabatabaee, S., Mahdiyar, A., Memari, A., & Ismail, S. (2019). Assessment of the building components in the energy efficient design of tropical residential buildings: An application of BIM and statistical Taguchi method. Energy, 188, Article 116080. https://doi.org/10.1016/j.energy.2019.116080

Sampaio, A. Z., Sequeira, P., & Gomes, A. M. 2023. Collaboration within architecture and structure based on BIM platforms. In Proceedings of 2023 18th Iberian Conference on Information Systems and Technologies (CISTI). IEEE. https://doi.org/10.23919/CISTI58278.2023.10211906

Sanchez, B., & Haas, C. (2018). A novel selective disassembly sequence planning method for adaptive reuse of buildings. Journal of Cleaner Production, 183, 998–1010. https://doi.org/10.1016/j.jclepro.2018.02.201

Santos, R., Costa, A. A., Silvestre, J. D., Vandenbergh, T., & Pyl, L. (2020). BIM-based life cycle assessment and life cycle costing of an office building in Western Europe. Building and Environment, 169, Article 106568. https://doi.org/10.1016/j.buildenv.2019.106568

Seyedzadeh, S., Rahimian, F. P., Oliver, S., Glesk, I., & Kumar, B. (2020a). Data driven model improved by multi-objective optimisation for prediction of building energy loads. Automation in Construction, 116, Article 103188. https://doi.org/10.1016/j.autcon.2020.103188

Seyedzadeh, S., Rahimian, F. P., Oliver, S., Rodriguez, S., & Glesk, I. (2020b). Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making. Applied Energy, 279, Article 115908. https://doi.org/10.1016/j.apenergy.2020.115908

Shi, X., Tian, Z., Chen, W., Si, B., & Jin, X. (2016). A review on building energy efficient design optimization rom the perspective of architects. Renewable and Sustainable Energy Reviews, 65, 872–884. https://doi.org/10.1016/j.rser.2016.07.050

Si, B., Tian, Z., Jin, X., Zhou, X., Tang, P., & Shi, X. (2016). Performance indices and evaluation of algorithms in building energy efficient design optimization. Energy, 114, 100–112. https://doi.org/10.1016/j.energy.2016.07.114

Sun, X., Shi, Z., Lei, G., Guo, Y., & Zhu, J. (2020). Multi-objective design optimization of an IPMSM based on multilevel strategy. IEEE Transactions on Industrial Electronics, 68(1), 139–148. https://doi.org/10.1109/TIE.2020.2965463

Tahmasebinia, F., Jiang, R., Sepasgozar, S., Wei, J., Ding, Y., & Ma, H. (2022). Using regression model to develop green building energy simulation by BIM tools. Sustainability, 14(10), Article 6262. https://doi.org/10.3390/su14106262

Tahmasebinia, F., He, R., Chen, J., Wang, S., & Sepasgozar, S. M. (2023). Building energy performance modeling through regression analysis: A case of Tyree Energy Technologies building at UNSW Sydney. Buildings, 13(4), Article 1089. https://doi.org/10.3390/buildings13041089

Theißen, S., Höper, J., Drzymalla, J., Wimmer, R., Markova, S., Meins-Becker, A., & Lambertz, M. (2020). Using open BIM and IFC to enable a comprehensive consideration of building services within a whole-building LCA. Sustainability, 12(14), Article 5644. https://doi.org/10.3390/su12145644

Tkalčić, D., Milovanović, B., Gaši, M., Jelčić Rukavina, M., & Banjad Pečur, I. (2023). Optimization of thermal bridges effect of composite lightweight panels with integrated steel load-bearing structure. Energies, 16(18), Article 6474. https://doi.org/10.3390/en16186474

Wang, C. L. (2010). Study on factors affecting energy consumption of large office building of the subtropical region energy [Master’s thesis]. Harbin Institute of Technology.

Wang, R., & Tang, Y. 2021. Research on parsing and storage of BIM information based on IFC standard. IOP Conference Series: Earth and Environmental Science, 643, Article 012172. https://doi.org/10.1088/1755-1315/643/1/012172

Wang, P., & Zhang, S. (2022). Retrofitting strategies based on orthogonal array testing to develop nearly zero energy buildings. Sustainability, 14(8), Article 4451. https://doi.org/10.3390/su14084451

Wang, J., Yu, C., & Pan, W. (2018). Life cycle energy of high-rise office buildings in Hong Kong. Energy and Buildings, 167, 152–164. https://doi.org/10.1016/j.enbuild.2018.02.038

Wei, T., & Chen, Y. (2020). Green building design based on BIM and value engineering. Journal of Ambient Intelligence and Humanized Computing, 11, 3699–3706. https://doi.org/10.1007/s12652-019-01556-z

Wi, S., Yang, S., Yun, B. Y., & Kim, S. (2021). Exterior insulation finishing system using cementitious plaster/microencapsulated phase change material for improving the building thermal storage performance. Construction and Building Materials, 299, Article 123932. https://doi.org/10.1016/j.conbuildmat.2021.123932

Wu, H. Y., Chang, B. G. & Zhu, C. C. (2001). A special case of genetic algorithm – orthogonal experimental design method. Journal of Software, 12(1), 148–153.

Xiang, Q.-C., Feng, X.-P., Jia, X.-Y., Cai, L., & Chen, R. (2019). Reducing carbon dioxide emissions through energy-saving renovation of existing buildings. Aerosol and Air Quality Research, 19(12), 2732–2745. https://doi.org/10.4209/aaqr.2019.10.0503

Xie, X., & Tu, J. 2021. Comparative study on energy consumption of AAC green prefabricated dwellings based on BIM technology. In Proceedings of International Conference on Smart Transportation and City Engineering 2021 (pp. 722–728). SPIE. https://doi.org/10.1117/12.2614234

Xu, X., Mumford, T., & Zou, P. X. (2021). Life-cycle building information modelling (BIM) engaged framework for improving building energy performance. Energy and Buildings, 231, Article 110496. https://doi.org/10.1016/j.enbuild.2020.110496

Yang, X., Liu, G., Li, Y., & Gao, S. (2021). Structural optimization of reciprocating seal with magnetic fluid based on orthogonal test design. Journal of Magnetics, 26(2), 229–237. https://doi.org/10.4283/JMAG.2021.26.2.229

Yao, G., Chen, Y., Xie, W., Chen, N., Rui, Y., & Luo, P. (2022). Research on collaborative design of performance-refined zero energy building: A case study. Energies, 15(19), Article 7185. https://doi.org/10.3390/en15197185

Yevu, S. K., Owusu, E. K., Chan, A. P., Oti-Sarpong, K., Wuni, I. Y., & Tetteh, M. O. (2023). Systematic review on the integration of building information modelling and prefabrication construction for low-carbon building delivery. Building Research & Information, 51(3), 279–300. https://doi.org/10.1080/09613218.2022.2131504

Yildirim, M., & Polat, H. (2023). Building information modeling applications in energy-efficient refurbishment of existing building stock: A case study. Sustainability, 15(18), Article 13600. https://doi.org/10.3390/su151813600

Yu, Z. (2023). Green building energy efficiency and landscape design based on remote sensing technology. Soft Computing. https://doi.org/10.1007/s00500-023-08515-z

Yuan, C., & Fan, Y. (2018). Research on data standard of green building information model based on IFC & its application. Journal of Information Technology in Civil Engineering and Architecture, 10(1), 9–15. https://doi.org/10.16670/j.cnki.cn11-5823/tu.2018.01.02

Yuce, B. E., Nielsen, P. V., & Wargocki, P. (2022). The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings. Building and Environment, 225, Article 109587. https://doi.org/10.1016/j.buildenv.2022.109587

Zhang, C., Nizam, R. S., & Tian, L. (2018). BIM-based investigation of total energy consumption in delivering building products. Advanced Engineering Informatics, 38, 370–380. https://doi.org/10.1016/j.aei.2018.08.009

Zhang, Y., Wang, W., Wang, Z., Gao, M., Zhu, L., & Song, J. (2021). Green building design based on solar energy utilization: Take a kindergarten competition design as an example. Energy Reports, 7, 1297–1307. https://doi.org/10.1016/j.egyr.2021.09.134

Zhao, T., Qu, Z., Liu, C., & Li, K. (2021). BIM-based analysis of energy efficiency design of building thermal system and HVAC system based on GB50189-2015 in China. International Journal of Low-Carbon Technologies, 16(4), 1277–1289. https://doi.org/10.1093/ijlct/ctab051

Zhu, Y., Liu, L., Qiu, Y., & Ma, Z. (2022). Design of the passive solar house in Qinba mountain area based on sustainable building technology in winter. Energy Reports, 8, 1763–1777. https://doi.org/10.1016/j.egyr.2022.03.026