Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Parece, S., Resende, R. & Rato, V. (2024). Addressing Material Efficiency in Building Renovation Scenarios, A BIM-based decision support tool. 2024 MIT Portugal Program Annual Conference: Ideias to Impact,.
Exportar Referência (IEEE) 
S. M. Parece et al.,  "Addressing Material Efficiency in Building Renovation Scenarios, A BIM-based decision support tool", in 2024 MIT Portugal Program Annu. Conf.: Ideias to Impact, 2024
Exportar BibTeX 
@misc{parece2024_1791517410964,
	author = "Parece, S. and Resende, R. and Rato, V.",
	title = "Addressing Material Efficiency in Building Renovation Scenarios, A BIM-based decision support tool",
	year = "2024",
	url = "https://mitportugal.mit.edu/poster-gallery/2024/student-posters/addressing-material-efficiency-building-renovation-scenarios-bim-based-decision-support-tool"
}
Exportar RIS 
TY  - CPAPER
TI  - Addressing Material Efficiency in Building Renovation Scenarios, A BIM-based decision support tool
T2  - 2024 MIT Portugal Program Annual Conference: Ideias to Impact
AU  - Parece, S.
AU  - Resende, R.
AU  - Rato, V.
PY  - 2024
UR  - https://mitportugal.mit.edu/poster-gallery/2024/student-posters/addressing-material-efficiency-building-renovation-scenarios-bim-based-decision-support-tool
AB  - Construction faces increasing sustainability performance, material and manpower scarcity and a growing shift into urban renovation processes, demanding time, cost and material efficiency. High-performing renovations can significantly reduce the building life cycle impact, but as Architects and Engineers transition to the BIM methodology, they find that computational tools and data to support sustainability and circular economy goals are primarily non-existing. This research aims to support informed decision-making on building renovation scenarios at early design phases from a circular material management perspective. The specific goals are: i) collect and define design criteria that guide construction designers to informed decisions, ii) develop BIM-based tools that identify the optimal design scenarios, and then iii) optimise the proposed tools with machine learning techniques. The expected results are a bim-based methodology that, through computational techniques, becomes more accurate over time and a database with the characterisation and environmental assessment of several renovation projects.
ER  -