Hou, Shangjie, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 and Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 2015. Ontology-based approach for structural design considering low embodied energy and carbon. Energy and Buildings 102 , pp. 75-90. 10.1016/j.enbuild.2015.04.051 |
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Abstract
Buildings account a large share of energy consumption and greenhouse gas emission. Numerous methods have been applied to operate buildings more efficiently. However, the embodied energy and carbon are identified increasingly important in terms of sustainability throughout building life cycle. In traditional building structural design approach, the engineers pay little attention on environmental aspect which has been recognised as one of the most important factors to consider in modern integrated building design approach. The emergence of Semantic Web technologies provides more opportunities to assist structural engineers in improving building sustainability. The study presented in this paper investigates how ontology and Semantic Web rules can be used in a knowledge-based system, to represent information about structural design and sustainability, and to facilitate decision-making in design process by recommending appropriate solutions for different situations. A prototypical system named OntoSCS (Sustainable Concrete Structure Ontology), including a Web Ontology Language (OWL) ontology as knowledge base and SWRL rules providing reasoning mechanism, is developed to offer optimised structural design solutions and selections of material suppliers. Embodied energy and CO2e are used in the system as indicators to evaluate sustainability of structure. Both ontology reasoner and case studies are employed for system validation.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Subjects: | T Technology > TD Environmental technology. Sanitary engineering T Technology > TH Building construction |
Uncontrolled Keywords: | Sustainable structural design; Ontology; SWRL; Embodied energy and carbon; Decision support system |
Publisher: | Elsevier |
ISSN: | 0378-7788 |
Date of First Compliant Deposit: | 30 March 2016 |
Date of Acceptance: | 28 April 2015 |
Last Modified: | 20 Nov 2024 00:15 |
URI: | https://orca.cardiff.ac.uk/id/eprint/73163 |
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