Literature DB >> 23177019

Monitoring and modeling of long-term settlements of an experimental landfill in Brazil.

Gustavo Ferreira Simões1, Cícero Antônio Antunes Catapreta.   

Abstract

Settlement evaluation in sanitary landfills is a complex process, due to the waste heterogeneity, time-varying properties and influencing factors and mechanisms, such as mechanical compression due to load application and creep, and physical-chemical and biological processes caused by the wastes decomposition. Many empirical models for the analysis of long-term settlement in landfills are reported in the literature. This paper presents the results of a settlement monitoring program carried out during 6 years in Belo Horizonte experimental landfill. Different sets of field data were used to calibrate three long-term settlement prediction models (rheological, hyperbolic and composite). The parameters obtained in the calibration were used to predict the settlements and to compare with actual field data. During the monitoring period of 6 years, significant vertical strains were observed (of up to 31%) in relation to the initial height of the experimental landfill. The results for the long-term settlement prediction obtained by the hyperbolic and rheological models significantly underestimate the settlements, regardless the period of data used in the calibration. The best fits were obtained with the composite model, except when 1 year field data were used in the calibration. The results of the composite model indicate settlements stabilization at larger times and with larger final settlements when compared to the hyperbolic and rheological models.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23177019     DOI: 10.1016/j.wasman.2012.10.001

Source DB:  PubMed          Journal:  Waste Manag        ISSN: 0956-053X            Impact factor:   7.145


  1 in total

1.  Multiple geophysical surveys for old landfill monitoring in Singapore.

Authors:  Ke Yin; Huanhuan Tong; Apostolos Giannis; Jing-Yuan Wang; Victor W-C Chang
Journal:  Environ Monit Assess       Date:  2016-12-15       Impact factor: 2.513

  1 in total

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