Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity
In the study described here model calibration was performed employing the inverse analysis using genetic algorithms (GA). The objective of analysis is to determine value of the coefficient of hydraulic conductivity, k. The commonly used method for the determination of coefficient of hydraulic conduc...
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Online Access: | https://doi.org/10.2478/sgem-2018-0013 |
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doaj-d5aa4a402c36402d8acafddb66c0017f2021-09-05T14:01:52ZengSciendoStudia Geotechnica et Mechanica2083-831X2018-08-0140214014610.2478/sgem-2018-0013sgem-2018-0013Application of Genetic Algorithms for the Estimation of Hydraulic ConductivityBartlewska-Urban M.0Strzelecki T.1Wrocław University of Technology, Faculty of Geoengineering, Mining and Geology, Wrocław, PolandWrocław University of Technology, Faculty of Technology And Natural Sciences, Wrocław, PolandIn the study described here model calibration was performed employing the inverse analysis using genetic algorithms (GA). The objective of analysis is to determine value of the coefficient of hydraulic conductivity, k. The commonly used method for the determination of coefficient of hydraulic conductivity based on Terzaghi consolidation leads to an underestimation of the value of k as the Terzaghi model does not take into account the deformation of soil skeleton. Here, an alternative methodology based on genetic algorithms is presented for the determination of the basic parameters of Biot consolidation model. It has been demonstrated that genetic algorithms are a highly effective tool enabling automatic calibration based on simple rules. The values of the coefficient of hydraulic conductivity obtained with GA are of at least one order smaller than values obtained with the Terzaghi model.https://doi.org/10.2478/sgem-2018-0013genetic algorithmshydraulic conductivitybiot consolidation model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bartlewska-Urban M. Strzelecki T. |
spellingShingle |
Bartlewska-Urban M. Strzelecki T. Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity Studia Geotechnica et Mechanica genetic algorithms hydraulic conductivity biot consolidation model |
author_facet |
Bartlewska-Urban M. Strzelecki T. |
author_sort |
Bartlewska-Urban M. |
title |
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity |
title_short |
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity |
title_full |
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity |
title_fullStr |
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity |
title_full_unstemmed |
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity |
title_sort |
application of genetic algorithms for the estimation of hydraulic conductivity |
publisher |
Sciendo |
series |
Studia Geotechnica et Mechanica |
issn |
2083-831X |
publishDate |
2018-08-01 |
description |
In the study described here model calibration was performed employing the inverse analysis using genetic algorithms (GA). The objective of analysis is to determine value of the coefficient of hydraulic conductivity, k. The commonly used method for the determination of coefficient of hydraulic conductivity based on Terzaghi consolidation leads to an underestimation of the value of k as the Terzaghi model does not take into account the deformation of soil skeleton. Here, an alternative methodology based on genetic algorithms is presented for the determination of the basic parameters of Biot consolidation model. It has been demonstrated that genetic algorithms are a highly effective tool enabling automatic calibration based on simple rules. The values of the coefficient of hydraulic conductivity obtained with GA are of at least one order smaller than values obtained with the Terzaghi model. |
topic |
genetic algorithms hydraulic conductivity biot consolidation model |
url |
https://doi.org/10.2478/sgem-2018-0013 |
work_keys_str_mv |
AT bartlewskaurbanm applicationofgeneticalgorithmsfortheestimationofhydraulicconductivity AT strzeleckit applicationofgeneticalgorithmsfortheestimationofhydraulicconductivity |
_version_ |
1717809429625176064 |