dc.contributor.author | Hosamo, Haidar | |
dc.date.accessioned | 2023-11-20T11:21:07Z | |
dc.date.available | 2023-11-20T11:21:07Z | |
dc.date.created | 2023-11-17T09:05:28Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Hosamo, H. (2023). Digital Twin technology toward more sustainable buildings [Doctoral dissertation]. University of Agder. | en_US |
dc.identifier.isbn | 978-82-8427-157-6 | |
dc.identifier.issn | 1504-9272 | |
dc.identifier.uri | https://hdl.handle.net/11250/3103539 | |
dc.description.abstract | The integration of digital technologies in the form of sensor networks and automation systems has a significant impact on the Architecture, Engineering, and Construction- Facility Management (AEC-FM) industry in terms of data monitoring and manage- ment. By combining the real and digital worlds, developments in digital technologies like Digital Twin provide a high-level depiction of buildings and their assets. This thesis covers a wide range of topics, including building information management and the interaction of building systems, where the Digital Twin technology becomes a solution to organizing data and generating new study lines on data interchange and BIM (Building Information Modeling)-FM interoperability. In order to contribute to digitalization and automation solutions for building management, the initial step in this thesis was to prepare a review of research on study patterns, gaps, and trends in the AEC-FM industry. After a complete bibliometric search of Google Scholar, Web of Science, and Scopus and following selection criteria, 77 academic publica- tions about the Digital Twin application in the AEC-FM industry were labeled and clustered accordingly. The results demonstrate that information standardization, predictive maintenance, users’ comfort, and optimizations are the marked fields where the Digital Twin in the AEC-FM industry should be implemented to reach Zero Emission Buildings (ZEB). This work suggests several novel frameworks for Digital Twin for building management as a place to start a further investigation. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Universitetet i Agder | en_US |
dc.relation.ispartof | Doctoral dissertations at University of Agder | |
dc.relation.ispartofseries | Doctoral dissertations at University of Agder;nr. 440 | |
dc.relation.haspart | Paper I: Hosamo, H., Imran, A., Cardenas-Cartagena, J., Svennevig, P. R., Svidt, K. & Nielsen, H. K. (2022) A Review of the Digital Twin Technology in the AEC-FM Industry. Advances in Civil Engineering, 2022, Article ID 2185170. https://doi.org/10.1155/2022/2185170. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3062346 | en_US |
dc.relation.haspart | Paper II: Hosamo, H., Svennevig, P. R., Svidt, K., Han, D. & Nielsen, H. K. (2022). A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics. Energy and Buildings, 261, 1-22. https://doi.org/10.1016/j.enbuild.2022.111988. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3062826 | en_US |
dc.relation.haspart | Paper III: Hosamo, H., Hosamo, M.H., Nielsen, H. K., Svennevig, P. R. & Svidt, K. (2022). Digital Twin of HVAC system (HVACDT) for multiobjective optimization of energy consumption and thermal comfort based on BIM framework with ANN-MOGA. Advances in Building Energy Research. https://doi.org/10.1080/17512549.2022.2136240. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3033389 | en_US |
dc.relation.haspart | Paper IV: Hosamo, H., Tingstveit, M.S., Nielsen, H.K., Svennevig, P.R. & Svidt, K. (2022). Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II. Energy and Buildings, 277, 1-23. https://doi.org/10.1016/j.enbuild.2022.112479. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3030680 | en_US |
dc.relation.haspart | Paper V: Hosamo, H., Nielsen, H.K., Alnmr, A., Svennevig, P.Rr. & Svidt, K. (2022). A review of the Digital Twin technology for fault detection in buildings. Frontiers in Built Environment, 8, 1-23. https://doi.org/10.3389/fbuil.2022.1013196 . Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3031107 | en_US |
dc.relation.haspart | Paper VI: Hosamo, H., Nielsen, H. K., Kraniotis, D., Svennevig, P. R. & Svidt, K. (2022). Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian buildings. Energy and Buildings, 281, 1-24. https://doi.org/10.1016/j.enbuild.2022.112732. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3042259 | en_US |
dc.relation.haspart | Paper VII: Hosamo, H., Nielsen, H. K., Kraniotis, D., Svennevig, P. R. & Svidt, K. (2023). Improving building occupant comfort through a digital twin approach: A Bayesian network model and predictive maintenance method. Energy and Buildings, 288, Artikkel 112992. https://doi.org/10.1016/j.enbuild.2023.112992. Published version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3098671 | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Digital Twin technology toward more sustainable buildings | en_US |
dc.title.alternative | Digital Twin technology toward more sustainable buildings | en_US |
dc.type | Doctoral thesis | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | © 2023 Haidar Hosamo Hosamo | en_US |
dc.subject.nsi | VDP::Teknologi: 500 | en_US |
dc.source.pagenumber | 351 | en_US |
dc.source.issue | 440 | en_US |
dc.identifier.cristin | 2197876 | |