Farid Fouchal_CIB W78 (LC3) Vol. 1 Heraklion Greece _ paper ready for submission_revised - 03Jun2017.pdf (174.92 kB)
Decision support tool for selection of best building retrofit action
conference contribution
posted on 2017-08-04, 10:47 authored by Farid Fouchal, Vanda Dimitriou, Tarek HassanTarek Hassan, Steven FirthSteven Firth, Argyris Oraiopoulos, Jonathan Masior, Sven SchimpfThis paper shows a process of developing a decision support tool to automatically generate building retrofit alternatives and rank them using energy performance analysis, user requirements, relevant benchmarks and regulations. Refinement of the retrofit scenarios follows a set of steps from creation of a Building Information Model of a base-case representing the status of the building at the time of the analysis, then creation of combinations for the possible retrofit scenarios. TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) based multi criteria approach is adopted as it relies on identified best alternatives using selected criteria. Ranking of alternatives follows their relative closeness to the identified ideal alternative. Best options are graphically presented.
Funding
The Design4Energy project is co-funded by the EU Commission, Information Society and Media Directorate-General, under the Seventh Framework Programme (FP7), Grant agreement no: 609380. Authors wish to acknowledge the Commission for their support.
History
School
- Architecture, Building and Civil Engineering
Published in
Joint Conference on Computing in Construction (JC3) Proceedings of the Joint Conference on Computing in Construction (JC3)Volume
1Pages
743 - 751 (9)Citation
FOUCHAL, F. ... et al, 2017. Decision support tool for selection of best building retrofit action. IN: Bosche, F., Brilakis, I. and Sacks, R. (eds). Lean and Computing in Construction Congress (LC3): Volume I - Proceedings of the Joint Conference on Computing in Construction (JC3), Heraklion, Greece, 4th-7th July 2017, pp. 741-749.Publisher
Heriot-Watt UniversityVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2017-05-30Publication date
2017Notes
This is a conference paper.ISBN
9780956595164Publisher version
Language
- en