The construction industry has been facing immense challenges to move towards more- sustainable buildings with minimum harm to the environment. The building design and construction process is conditioned by numerous sustainability regulations and assessment measures, to promote sustainable construction. These regulations are continuously expanding in their requirements, and incorporating a huge amount of data that needs to be rigorously dealt with, in order to check compliance and asses the performance Building Information Modelling (BIM) promotes the effective information and process integration across the building life-cycle and supply chain. This integration should comply with an increasingly-complex regulatory environment and statutory requirements. The aim of this thesis is to improve and facilitate the sustainability compliance checking process, by focusing on inter-operability between existing methods of compliance checking and building information modelling. This thesis presents a generic approach for BIM based compliance checking against standards and regulations, with a particular focus on sustainable design and procurement. To achieve this, a methodology has been developed to enable automated sustainability compliance checking. This involves (a) extracting regulatory requirements from sustainability-related regulations available in textual format; (b) converting these into BIM- compatible rules; (c) processing these rules through a dedicated rule-based service; and (d) performing regulatory compliance analysis underpinned by the concept of BIM. A semantic extension of the IFC (Industrial Foundation Classes) for sustainability compliance checking has been developed. The outcome of the research was implemented in the RegBIM project and is in the process of being exploited as an online service by industrial organization, the Building Research Establishment (BRE) in the UK.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:667917 |
| Date | January 2015 |
| Creators | Kasim, Tala |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/78325/ |
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