IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i10p2956-d558436.html
   My bibliography  Save this article

A Procedure for Automating Energy Analyses in the BIM Context Exploiting Artificial Neural Networks and Transfer Learning Technique

Author

Listed:
  • Mikhail Demianenko

    (Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy)

  • Carlo Iapige De Gaetani

    (Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy)

Abstract

One of the main benefits of Building Information Modelling is the capability of improving the decision-making process thanks performing what-if tests on digital twins of the building to be realized. Pairing BIM models to Building Energy Models allows designers to determine in advance the energy consumption of the building, improving sustainability of the construction. The challenge is to consider as many elements involved in the energy balance as possible and shuffling their parameters within a certain range. In this work, the automatic creation of a relevant set of design options to be analyzed for searching the optimum has been carried out. Firstly, the usual workflow that would be applied manually has been automatically followed by running scripts and codes, depending just on the initial setup given by the user. Although the procedure is very resource consuming, the main advancement relies in the reduction of the manual intervention and the possibility of creating large datasets of design options, avoiding gross errors. Secondly, Artificial Neural Networks and Transfer Learning techniques are applied to speed up the process of dataset creation. With such approach, the same dataset has been created, with about 30% of initial data and without significant loss of accuracy.

Suggested Citation

  • Mikhail Demianenko & Carlo Iapige De Gaetani, 2021. "A Procedure for Automating Energy Analyses in the BIM Context Exploiting Artificial Neural Networks and Transfer Learning Technique," Energies, MDPI, vol. 14(10), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2956-:d:558436
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/10/2956/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/10/2956/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jitka Mohelníková & Miloslav Novotný & Pavla Mocová, 2020. "Evaluation of School Building Energy Performance and Classroom Indoor Environment," Energies, MDPI, vol. 13(10), pages 1-17, May.
    2. Mohammad K. Najjar & Vivian W. Y. Tam & Leandro Torres Di Gregorio & Ana Catarina Jorge Evangelista & Ahmed W. A. Hammad & Assed Haddad, 2019. "Integrating Parametric Analysis with Building Information Modeling to Improve Energy Performance of Construction Projects," Energies, MDPI, vol. 12(8), pages 1-22, April.
    3. Carlo Iapige De Gaetani & Andrea Macchi & Pasquale Perri, 2020. "Joint Analysis of Cost and Energy Savings for Preliminary Design Alternative Assessment," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    4. Kamel, Ehsan & Memari, Ali M., 2018. "Automated Building Energy Modeling and Assessment Tool (ABEMAT)," Energy, Elsevier, vol. 147(C), pages 15-24.
    5. Cristina Piselli & Jessica Romanelli & Matteo Di Grazia & Augusto Gavagni & Elisa Moretti & Andrea Nicolini & Franco Cotana & Francesco Strangis & Henk J. L. Witte & Anna Laura Pisello, 2020. "An Integrated HBIM Simulation Approach for Energy Retrofit of Historical Buildings Implemented in a Case Study of a Medieval Fortress in Italy," Energies, MDPI, vol. 13(10), pages 1-21, May.
    6. Guofeng Ma & Ying Liu & Shanshan Shang, 2019. "A Building Information Model (BIM) and Artificial Neural Network (ANN) Based System for Personal Thermal Comfort Evaluation and Energy Efficient Design of Interior Space," Sustainability, MDPI, vol. 11(18), pages 1-26, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Coraci, Davide & Brandi, Silvio & Hong, Tianzhen & Capozzoli, Alfonso, 2023. "Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings," Applied Energy, Elsevier, vol. 333(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Linyan Chen & Xin Gao & Shitao Gong & Zhou Li, 2020. "Regionalization of Green Building Development in China: A Comprehensive Evaluation Model Based on the Catastrophe Progression Method," Sustainability, MDPI, vol. 12(15), pages 1-22, July.
    2. Suzana Domjan & Sašo Medved & Boštjan Černe & Ciril Arkar, 2019. "Fast Modelling of nZEB Metrics of Office Buildings Built with Advanced Glass and BIPV Facade Structures," Energies, MDPI, vol. 12(16), pages 1-18, August.
    3. Karim Mohamed Ragab & Mehmet Fatih Orhan & Kenan Saka & Yousef Zurigat, 2022. "A Study and Assessment of the Status of Energy Efficiency and Conservation at School Buildings," Sustainability, MDPI, vol. 14(17), pages 1-31, August.
    4. Mohammad K. Najjar & Eduardo Linhares Qualharini & Ahmed W. A. Hammad & Dieter Boer & Assed Haddad, 2019. "Framework for a Systematic Parametric Analysis to Maximize Energy Output of PV Modules Using an Experimental Design," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    5. Cristina Piselli & Alessio Guastaveglia & Jessica Romanelli & Franco Cotana & Anna Laura Pisello, 2020. "Facility Energy Management Application of HBIM for Historical Low-Carbon Communities: Design, Modelling and Operation Control of Geothermal Energy Retrofit in a Real Italian Case Study," Energies, MDPI, vol. 13(23), pages 1-18, December.
    6. Cristina Piselli & Jessica Romanelli & Matteo Di Grazia & Augusto Gavagni & Elisa Moretti & Andrea Nicolini & Franco Cotana & Francesco Strangis & Henk J. L. Witte & Anna Laura Pisello, 2020. "An Integrated HBIM Simulation Approach for Energy Retrofit of Historical Buildings Implemented in a Case Study of a Medieval Fortress in Italy," Energies, MDPI, vol. 13(10), pages 1-21, May.
    7. Ngoc-Son Truong & Duc Long Luong & Quang Trung Nguyen, 2023. "BIM to BEM Transition for Optimizing Envelope Design Selection to Enhance Building Energy Efficiency and Cost-Effectiveness," Energies, MDPI, vol. 16(10), pages 1-24, May.
    8. Jungsik Choi & Sejin Lee, 2023. "A Suggestion of the Alternatives Evaluation Method through IFC-Based Building Energy Performance Analysis," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    9. Marek Dudzik, 2020. "Towards Characterization of Indoor Environment in Smart Buildings: Modelling PMV Index Using Neural Network with One Hidden Layer," Sustainability, MDPI, vol. 12(17), pages 1-37, August.
    10. Flavio Rosa, 2020. "Building-Integrated Photovoltaics (BIPV) in Historical Buildings: Opportunities and Constraints," Energies, MDPI, vol. 13(14), pages 1-28, July.
    11. Hanan S.S. Ibrahim & Ahmed Z. Khan & Waqas Ahmed Mahar & Shady Attia & Yehya Serag, 2021. "Assessment of Passive Retrofitting Scenarios in Heritage Residential Buildings in Hot, Dry Climates," Energies, MDPI, vol. 14(11), pages 1-27, June.
    12. Kočí, Jan & Kočí, Václav & Maděra, Jiří & Černý, Robert, 2019. "Effect of applied weather data sets in simulation of building energy demands: Comparison of design years with recent weather data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 22-32.
    13. Sangmu Bae & Yujin Nam & Joon-Ho Choi, 2020. "Comparative Analysis of System Performance and Thermal Comfort for an Integrated System with PVT and GSHP Considering Two Load Systems: Convective Heating and Radiant Floor Heating," Energies, MDPI, vol. 13(20), pages 1-19, October.
    14. Carlo Iapige De Gaetani & Andrea Macchi & Pasquale Perri, 2020. "Joint Analysis of Cost and Energy Savings for Preliminary Design Alternative Assessment," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    15. Gao, Hao & Koch, Christian & Wu, Yupeng, 2019. "Building information modelling based building energy modelling: A review," Applied Energy, Elsevier, vol. 238(C), pages 320-343.
    16. Heap-Yih Chong & Mengyuan Cheng, 2023. "Integrating Advanced Technologies for Sustainable Construction Purposes," Energies, MDPI, vol. 16(16), pages 1-4, August.
    17. Simone Forastiere & Cristina Piselli & Benedetta Pioppi & Carla Balocco & Fabio Sciurpi & Anna Laura Pisello, 2023. "Towards Achieving Zero Carbon Targets in Building Retrofits: A Multi-Parameter Building Information Modeling (BIM) Approach Applied to a Case Study of a Thermal Bath," Energies, MDPI, vol. 16(12), pages 1-23, June.
    18. Abdelali Agouzoul & Emmanuel Simeu & Mohamed Tabaa, 2024. "Advancing Sustainable Building Practices: Intelligent Methods for Enhancing Heating and Cooling Energy Efficiency," Sustainability, MDPI, vol. 16(7), pages 1-29, March.
    19. Eun Soo Park & Hee Chang Seo, 2021. "Risk Analysis for Earthquake-Damaged Buildings Using Point Cloud and BIM Data: A Case Study of the Daeseong Apartment Complex in Pohang, South Korea," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    20. Ziyi Zhang & Yiquan Zou, 2022. "Research hotspots and trends in heritage building information modeling: A review based on CiteSpace analysis," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-22, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2956-:d:558436. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.