Non-graphical data structure for the purpose of BIM-based Life Cycle Assessment: Methodology for the Czech environment
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Date
2020-12-15
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Mark
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IOP Publishing
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Abstract
The article deals with the data structure for the purpose of life cycle assessment of buildings using the Building Information Model (BIM), for implementation in the Czech construction industry. Construction industry produces a significant amount of waste while the capacity of landfills is being limited. Effective management of already used materials, that have the potential to be reused, can significantly help to decrease consumption and save natural resources. Life Cycle Assessment (LCA) is a method that can be used to demonstrate the suitability of proposed materials, structures, or buildings in terms of their whole life cycle and its environmental impact. For the LCA evaluation it is crucial to obtain life cycle inventory (LCI) input data, however, the structure of this data is not clearly defined for the Czech environment. The BIM includes, in addition to geometry, the information part applicable to this assessment. The aim of the article is to analyse previous approaches and to define a BIM data structure for LCI purposes of a particular material. The new methodology is based on standardization of non-graphic information model data structure, called SNIM, which was developed for the Czech construction industry. From the SNIM database, "mark-up syntaxes" has been taken over to further identify the data for LCI base structure purposes. The MatLab matrix solver was used to classify these data. Advantages of the proposed methodology have been demonstrated on the case study of monolithic concrete slab structure, in which three types of concrete were evaluated. The results indicated the percentage of impact categories for each concrete type. These results are useful for expanding the BIM model with new data necessary for further LCA calculations. BIM model, extended by LCA calculation, will lead to a reduction of natural resources extraction as well as positive impact on environment.
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IOP Conference Series: Earth and Environmental Science. 2020, vol. 609, p. 1-9.
https://iopscience.iop.org/article/10.1088/1755-1315/609/1/012048
https://iopscience.iop.org/article/10.1088/1755-1315/609/1/012048
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Peer-reviewed
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en