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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 81
PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: B.H.V. Topping
Paper 252

Inverse Analysis of an Embankment on Soft Clay using the Ensemble Kalman Filter

A. Hommels+, F. Molenkamp+, B. Nguyen$ and A.W. Heemink*

+Faculty of Civil Engineering and Geosciences, Section of GeoEngineering
*Faculty of Electrical Engineering, Mathematics and Computer Science, Delft Institute of Applied Mathematics
Delft Technical University, The Netherlands
$Netherlands Organisation for Applied Scientific Research TNO, Netherlands Institute of Applied Geoscience NITG, Utrecht, The Netherlands

Full Bibliographic Reference for this paper
A. Hommels, F. Molenkamp, B. Nguyen, A.W. Heemink, "Inverse Analysis of an Embankment on Soft Clay using the Ensemble Kalman Filter", in B.H.V. Topping, (Editor), "Proceedings of the Tenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 252, 2005. doi:10.4203/ccp.81.252
Keywords: inverse modelling, soil properties, Ensemble Kalman filter.

Summary
This paper shows that the Ensemble Kalman filter can be a very powerful inverse modelling technique in the field of geomechanics.

Geomechanical models are indispensable for reliable design of engineering structures and processes and hazard and risk evaluation. These models are however far from perfect. Errors are introduced by fluctuations in the input or by poorly known parameters in the model. To overcome these problems an inverse modelling technique to incorporate measurements into the deterministic model to improve the model results can be implemented. This allows for observations of on-going processes to be used for enhancing the quality of subsequent model predictions.

In geomechanics several examples of inverse modelling exist where the improved model of the system is obtained by minimizing the discrepancy between the observed values in the system and the modelled state of the system within a certain time interval [1,2,5,6,7,8,9]. This requires the implementation of the adjoint model. Even with the use of the adjoint compilers that have become available recently, this is a tremendous programming effort for the existing geomechanical model system.

Therefore, the Ensemble Kalman filter [3,4] is implemented to overcome this problem. The Ensemble Kalman filter is already rather common in meteorology and oceanography and the state of the system is analysed each time data becomes available. An additional challenge is to incorporate the influence of the heterogeneity of the ground.

Very promising results of a conceptual example, based on the construction of a road embankment on soft clay, are presented. Also the effect of incorporating measurement noise is shown as well as the importance of the location of the observation points. In the near future, the Ensemble Kalman filter is not only used for a straight forward identification of the elastic modulus E and the K0 parameter of several soil layers below the embankment, but also incorporates the uncertainty of the exact location of the boundaries between the subsequent layers.

References
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Honjo, Y., Liu, W.T. and Soumitra, G., "Inverse analysis of an embankment on soft clay by extended Bayesian method". Int. Journal for Num. and Anal. Methods in Geomechanics, vol. 18, 709-734 (1994a). doi:10.1002/nag.1610181004
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