A continous Bayesian network for earth dams' risk assessment: methodology and quantification
article
Dams’ safety is highly important for authorities around the world. The impacts of a dam failure can be enormous. Models for
investigating dam safety are required for helping decision-makers to mitigate the possible adverse consequences of flooding.
A model for earth dam safety must specify clearly possible contributing factors, failure modes and potential consequences of
dam failure. Probabilistic relations between variables should also be specified. Bayesian networks (BNs) have been
identified as tools that would assist dam engineers on assessing risks. BNs are graphical models that facilitate the
construction of a joint probability distribution. Most of the time, the variables included in a model for earth dam risk
assessment involve continuous quantities. The presence of continuous random variables makes the implementation of
discrete BNs difficult. An alternative to discrete BNs is the use of non-parametric continuous BNs, which will be briefly
described in this article. As an example, a model for earth dams’ safety in the State of Mexico will be discussed. Results
regarding the quantification of conditional rank correlations through ratios of unconditional rank correlations have not been
presented before and are introduced herein. While the complete application of the model for the State of Mexico is presented
in an accompanying paper, here some results regarding model use are shown for demonstration purposes. The methods
presented in this article can be applied for investigating risks of failure of civil infrastructures other than earth dams.
investigating dam safety are required for helping decision-makers to mitigate the possible adverse consequences of flooding.
A model for earth dam safety must specify clearly possible contributing factors, failure modes and potential consequences of
dam failure. Probabilistic relations between variables should also be specified. Bayesian networks (BNs) have been
identified as tools that would assist dam engineers on assessing risks. BNs are graphical models that facilitate the
construction of a joint probability distribution. Most of the time, the variables included in a model for earth dam risk
assessment involve continuous quantities. The presence of continuous random variables makes the implementation of
discrete BNs difficult. An alternative to discrete BNs is the use of non-parametric continuous BNs, which will be briefly
described in this article. As an example, a model for earth dams’ safety in the State of Mexico will be discussed. Results
regarding the quantification of conditional rank correlations through ratios of unconditional rank correlations have not been
presented before and are introduced herein. While the complete application of the model for the State of Mexico is presented
in an accompanying paper, here some results regarding model use are shown for demonstration purposes. The methods
presented in this article can be applied for investigating risks of failure of civil infrastructures other than earth dams.
TNO Identifier
469127
Source
Structure and Infrastructure Engineering, pp. 1-16.
Pages
1-16
Files
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