<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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, <italic>k</italic>. The commonly used method for the determination of coefficient of hydraulic conductivity based on Terzaghi consolidation leads to an underestimation of the value of <italic>k</italic> 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.</p></abstract>

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.

Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity

Studia Geotechnica et Mechanica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"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...

Exp. no	k [10^-11m/s]	Exp. no	k [10^-11m/s]
1	70.52	11	62.43
2	63.06	12	75.83
3	61.44	13	61.23
4	66.63	14	61.12
5	62.43	15	65.01
6	71.05	16	60.39
7	60.70	17	61.85
8	65.01	18	62.43
9	66.58	19	62.43
10	61.85	20	72.94

Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity

Article Category: Research Article

Published Online: Aug 04, 2018

Page range: 140 - 146

Received: Oct 21, 2017

Accepted: May 28, 2018

DOI: https://doi.org/10.2478/sgem-2018-0013

Keywords
genetic algorithms, hydraulic conductivity, Biot consolidation model

© 2018 M. Bartlewska-Urban, T. Strzelecki, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

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Figure 8

Parameter estimation results.

Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity

Article Category: Research Article

Published Online: Aug 04, 2018

Page range: 140 - 146

Received: Oct 21, 2017

Accepted: May 28, 2018

DOI: https://doi.org/10.2478/sgem-2018-0013

Keywordsgenetic algorithms, hydraulic conductivity, Biot consolidation model

© 2018 M. Bartlewska-Urban, T. Strzelecki, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Parameter estimation results.

Keywords
genetic algorithms, hydraulic conductivity, Biot consolidation model