Content area

Abstract

The present work assesses the feasibility of using mining and industrial residues as aggregates of coating mortars in terms of building thermal performance. For this purpose, we investigated four types of aggregates (river sand—REF, iron ore tailings—IOT, friable quartzite—QTZ, and steelmaking slag—SLG). Initially, the specific gravity (density) and thermal conductivity of the residue-based mortars were experimentally obtained. Subsequently, a sensitivity analysis was performed through energy simulations of two existing dwellings. Mortars with SLG and IOT presented the best performance due to their low thermal conductivity and, more importantly, their high density. Mortars with SLG presented 64% of thermal performance classifications as “superior” and “intermediate”, versus an average of 53% for the other aggregates. They were followed by those with IOT, REF and lastly those with QTZ. Therefore, these mortars are cost-effective and sustainable solutions to passively improve the thermal performance of buildings, as well as to mitigate the impacts of the disposal of these residues.

Details

Title
Coating mortars based on mining and industrial residues
Author
Castro Mendes Júlia 1   VIAFID ORCID Logo  ; Barreto, Rodrigo Rony 1 ; de Freitas Vilaça Vanessa 2 ; Lopes, Amanda Vitor 2 ; de Souza Henor Artur 3 ; Peixoto Ricardo André Fiorotti 1 

 Federal University of Ouro Preto, Laboratório de Materiais de Construção Civil, Department of Civil Engineering, Ouro Preto, Brazil (GRID:grid.411213.4) (ISNI:0000 0004 0488 4317) 
 Federal University of Ouro Preto, Department of Architecture and Urban Planning, Ouro Preto, Brazil (GRID:grid.411213.4) (ISNI:0000 0004 0488 4317) 
 Federal University of Ouro Preto, Department of Mechanical Engineering, Ouro Preto, Brazil (GRID:grid.411213.4) (ISNI:0000 0004 0488 4317) 
Pages
1569-1586
Publication year
2020
Publication date
Sep 2020
Publisher
Springer Nature B.V.
ISSN
14384957
e-ISSN
16118227
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2438134103
Copyright
© Springer Japan KK, part of Springer Nature 2020.