MVD based information exchange between BIM and building energy performance simulation

Pinheiro, Sérgio Veloso Brant; Wimmer, Reinhard; O’Donnell, James; Muhič, Sergej; Bazjanac, Vladimir; Maile, Tobias; Frisch, Jérôme; Treeck, Christoph van

doi:10.1016/j.autcon.2018.02.009

Cited by 110 publications

(48 citation statements)

References 9 publications

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“…In a similar context, [60] examined the use of BIM and BPS tools to facilitate energy-efficient buildings. A standardised approach for integrating information from BIM and BPS tools, via Industry Foundation Classes (IFC) schema was proposed in [61]. In [62], acoustic performance monitoring via use of semantic rule checking was implemented for a building model.…”

Section: Bim In Building Performancementioning

confidence: 99%

Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

Hammad

2019

Buildings

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Building energy performance tools are widely used to simulate the expected energy consumption of a given building during the operation phase of its life cycle. Deviations between predicted and actual energy consumptions have however been reported as a major limiting factor to the tools adopted in the literature. A significant reason highlighted as greatly influencing the difference in energy performance is related to the occupant behaviour of the building. To enhance the effectiveness of building energy performance tools, this study proposes a method which integrates Building Information Modelling (BIM) with artificial neural network model for limiting the deviation between predicted and actual energy consumption rates. Through training a deep neural network for predicting occupant behaviour that reflects the actual performance of the building under examination, accurate BIM representations are produced which are validated via energy simulations. The proposed method is applied to a realistic case study, which highlights significant improvements when contrasted with a static simulation that does not account for changes in occupant behaviour.

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Section: Bim In Building Performancementioning

confidence: 99%

Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

Hammad

2019

Buildings

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“…For its development, other supporting tools, relevant libraries and an MVD XML for conventional BEPS have been created. Other attempts in this domain have been primarily focused on developing a MVD XML for conventional and advanced BEPS (Pinheiro et al 2018). The initial processes and the three main stages of the workflow are described analytically in the following sections.…”

Section: Proposed Ifc4 Workflowmentioning

confidence: 99%

An IFC data preparation workflow for building energy performance simulation

Katsigarakis¹,

Giannakis²,

Lilis³

et al. 2019

Computing in Construction

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Accurate building energy performance simulation model generation from IFC data files require the input IFC data to be correct and complete. To ensure such data quality conditions, methods integrating IFC data correctness and completeness checks, under a common architecture, are introduced. IFC data correctness is supported by the use of a dedicated geometric error detection tool, which identifies and reports back to the building designer, errors affecting the building's 2 nd -level space boundary topology. IFC data completeness is performed by the use of a dedicated for building energy performance simulation Model View Definition schema. The quality checking results are reported in a BIM collaboration file format.

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“…The required classes are selected and added to the ACEie exchange model. Although the IFC4 schema has enriched the level of detail of several assets, such as boilers, it still lacks additional classifications for some assets instead of using generic classes (Pinheiro et al, 2018). To overcome this limitation, both air-handling units and fan-cooling units were mapped to IfcAirToAirHeatRecovery and also all of the kitchen assets were mapped to IfcElectricAppliance.…”

Section: Aceie Mvdmentioning

confidence: 99%

Semantic and syntactic interoperability of BIM and asset management data

Farghaly¹,

Abanda²,

Vidalakis³

et al. 2019

Computing in Construction

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Over the recent years, there has been a growing interest in how Building Information Modelling (BIM) can facilitate effective Asset Management (AM). BIM-AM data integration has come with issues related to establishing an effective process to extract, store, and distribute data to ensure interoperability. Several information exchange specifications such as COBie and SPARKie have been developed to enable effective interoperability for better building assets operation and maintenance. Due to asset heterogeneity, the exchange models cannot be generalized and applied to all assets systems. Exchange models need to be developed for particular asset systems based on their functionality and building type. In order to contribute to overcoming the BIM-AM interoperability challenge, this study aims to provide the required semantic and syntactic interoperability aspects for the data exchange of assets that consume energy from the BIM systems to the AM systems during the handover stage.

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MVD based information exchange between BIM and building energy performance simulation

Cited by 110 publications

References 9 publications

Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

An IFC data preparation workflow for building energy performance simulation

Semantic and syntactic interoperability of BIM and asset management data

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