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A neural network approach to predict the performance of recycled concrete used in permeable reactive barriers for the treatment of acidic groundwater

B. Guruprasad, B. Indraratna, L. D. Nghiem and G. Regmi
A neural network approach to predict the performance of recycled concrete used in permeable reactive barriers for the treatment of acidic groundwater
Quarterly Journal of Engineering Geology and Hydrogeology (May 2011) 44 (2): 199-209

Abstract

This study developed a neural network model for examining the performance of recycled concrete for the treatment of acidic groundwater. Concentrations of Al, Fe and Ca and alkalinity of the effluent were selected as the output parameters to simulate the performance of recycled concrete for neutralizing acidic groundwater. The input variables were the number of pore volumes, pH, oxidation reduction potential and the average hydraulic conductivity. Of the 658 experimental datasets available, 409 datasets were used for training, 184 datasets were used for validation, and the remaining datasets were used for cross-validation. The reported results indicate that the neural model is a valuable tool to assess and simulate the performance of recycled concrete. The sensitivity study confirmed that the selected input signals of the output estimate were equally important. A similar model could also be used for full-scale permeable reactive barrier installation provided that up-scaling issues such as the possible non-homogeneous nature of the recycled concrete and variation in groundwater quality can be effectively resolved.


ISSN: 1470-9236
EISSN: 2041-4803
Serial Title: Quarterly Journal of Engineering Geology and Hydrogeology
Serial Volume: 44
Serial Issue: 2
Title: A neural network approach to predict the performance of recycled concrete used in permeable reactive barriers for the treatment of acidic groundwater
Affiliation: University of Wollongong, School of Civil, Mining and Environmental Engineering, Wollongong, N.S.W., Australia
Pages: 199-209
Published: 201105
Text Language: English
Publisher: Geological Society of London, London, United Kingdom
References: 29
Accession Number: 2011-048427
Categories: Environmental geology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 4 tables
Country of Publication: United Kingdom
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data from The Geological Society, London, London, United Kingdom
Update Code: 201127
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