DOI: 10.1016/j.jclepro.2019.119283
论文题名: Eco-friendly mortars with addition of ornamental stone waste - A mathematical model approach for granulometric optimization
作者: Amaral L.F. ; Girondi Delaqua G.C. ; Nicolite M. ; Marvila M.T. ; de Azevedo A.R.G. ; Alexandre J. ; Fontes Vieira C.M. ; Monteiro S.N.
刊名: Journal of Cleaner Production
ISSN: 9596526
出版年: 2020
卷: 248 语种: 英语
英文关键词: Cementitious mortar
; Granulometric optimization
; Particle size distribution
; Rock-processing waste
Scopus关键词: Aggregates
; Environmental protection
; Fossil fuel deposits
; Fossil fuels
; Global warming
; Hardening
; Light transmission
; Lime
; Particle size
; Particle size analysis
; Pollution control
; Portland cement
; Sand
; Size distribution
; Cementitious composites
; Cementitious materials
; Cementitious mortars
; Chemical compositions
; Global warming and climate changes
; Rock processing
; Technological characterizations
; Technological properties
; Mortar
英文摘要: The increasing production of cementitious materials is generating considerable environmental impacts related to uncontrolled extraction of natural raw material for use as aggregates and the consumption of mostly fossil fuel based energy resources in the cement production. Moreover, Portland cement fabrication is highly energy intensive and releases one of the word's largest rate of CO2 emission, the main responsible for global warming and climate changes. Mortar is a typical example of a cementitious material associated with these environmental impacts. Among the possibilities for a mortar cleaner production stands the reduction of natural aggregates in their preparation, such as sand. Therefore, the objective of this work is to propose a methodology of partial replacement of the sand, commonly used for mortar production, by ornamental stone-processing waste. For this purpose, a mathematical model was applied to calculate the ideal particle size distribution for better packaging, which not only justify the replacement but also improve the technological properties of the mortar as a cementitious composite material. Mortars were made with a 1: 1: 6 compositions, associated with cement: lime: sand proportions. Amounts of 9 and 21 wt% of sand were replaced by waste, corresponding to values obtained through the mathematical model. These mortar precursor materials were characterized in terms of granulometry, chemical composition, pozolanicity as well as leaching and solubilization tests. The mortar technological characterization was performed both in its initial state (fresh density, air content and consistency) and past-cure hardened state (hardened density, flexural and compression stress). The results indicated the possibility of producing more sustainable and eco-friendly mortars. Moreover, this work also evidences that, in addition to the possibility of using ornamental stone waste as aggregate for cementitious materials, the particle size model is a non-empirical means to optimize aggregate mixtures and to improve the properties of waste incorporated eco-friendly mortars. © 2019 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158899
Appears in Collections: 气候变化与战略
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作者单位: UENF - State University of the Northern Rio de Janeiro, LAMAV – Advanced Materials Laboratory, Av. Alberto Lamego, 2000, Campos dos Goytacazes, 28013-602, Brazil; UENF - State University of the Northern Rio de Janeiro, LECIV – Civil Engineering Laboratory, Av. Alberto Lamego, 2000, Campos dos Goytacazes, 28013-602, Brazil; UFF - Federal Fluminense University, TER – Department of Agricultural and Environmental Engineering, Rua Passo da Pátria, 156, Niterói, Brazil; IME - Military Institute of Engineering - IME, Department of Materials Science, Praça General Tibúrcio, 80, Praia Vermelha, Urca, RJ, Rio de Janeiro, RJ 22290-270, Brazil
Recommended Citation:
Amaral L.F.,Girondi Delaqua G.C.,Nicolite M.,et al. Eco-friendly mortars with addition of ornamental stone waste - A mathematical model approach for granulometric optimization[J]. Journal of Cleaner Production,2020-01-01,248