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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 91
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: B.H.V. Topping, L.F. Costa Neves and R.C. Barros
Paper 224

Using an Artificial Intelligence Method to Model the Behaviour of Embankment Dams

C. Curt1, M. Le Goc2 and R. Tourment1

1Cemagref, Hydraulics Engineering and Hydrology Research Unit, Aix-en-Provence, France
2Laboratory of Sciences of Information and Systems, Marseille, France

Full Bibliographic Reference for this paper
C. Curt, M. Le Goc, R. Tourment, "Using an Artificial Intelligence Method to Model the Behaviour of Embankment Dams", in B.H.V. Topping, L.F. Costa Neves, R.C. Barros, (Editors), "Proceedings of the Twelfth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 224, 2009. doi:10.4203/ccp.91.224
Keywords: dam, safety, behaviour, multi modelling, diagnosis, control, prognosis.

Summary
Reliability and safety of dams must be controlled through their whole life to guarantee the safety of the people and assets located at their downstream, and to insure they fulfil the functions for which they were built and to safeguard these infrastructures. As a consequence, it is necessary to develop methods and tools for the control of the reliability and safety of dams. In particular, tasks related to the assessment, the diagnosis and the prognosis of dam behaviour are very important to prevent accidents and determine corrective actions.

The analysis and control of the dam's behaviour, with the aim of controlling the reliability and safety, require the development of models that represent the dynamics of dams. These models have to represent the complexity of the dam behaviour while being easy to handle and to instantiate to the whole set of dams that present different features. They must admit miscellaneous data as inputs. Finally, these models must be adequate to carry out diagnosis or prognosis tasks to improve dam reliability and safety.

In this paper, a multi-model approach is proposed to consider the past, the present and the future behaviour of a dam. This multi-model approach combines the ideas of Chittaro et al. [1] with Zanni's conceptual framework [2]. Our approach is based on four models: a structural model describing relations between components, a functional model describing the relations which determine the assignment of a possible value to a variable, a behavioural model describing the states of the system and the discrete events that represent the state transitions and a perception model that defines the process and its operating modes. These models were validated by a panel of experts. The method was applied to a real case study concerning a dam which suffered from an internal erosion mechanism.

These models were developed to carry out diagnosis, assessment, prognosis and control tasks. Currently, our work shows that the models developed are relevant to perform assessment and diagnosis tasks. Moreover, the multi-model approach presents the advantage to facilitate the knowledge representation and handling as well as the results communication to owners or reservoir operators. One of the perspectives is to use the models to forecast dam reliability and safety through time.

References
1
L. Chittaro, G. Guida, C. Tasso, E. Toppano, "Functional and teological knowledge in the multimodeling approach for reasoning about physical systems: A case study in diagnosis", IEEE Transactions on Systems, Man, and Cybernetics, Vol 23, pp 1718-1751, 1993. doi:10.1109/21.257765
2
C. Zanni, M. Le Goc, C. Frydman, "A conceptual framework for the analysis, classification and choice of knowledge-based diagnosis systems", International Journal of Knowledge-based and Intelligent Engineering Systems, Vol 10, pp 113-138, 2006.

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