I am happy to announce that our pre-print paper, “Calibration of the von Wolffersdorff model using Genetic Algorithms”, is available on researchgate:


In this article, we propose a novel algorithm for the automatic calibration of von Wolffersdorff’s Sand Hypoplasticity (SH) model. This algorithm is based on Genetic Algorithm (GA) optimization and consists of solving the regression problem of identifying the model parameters from the dataset produced by triaxial and eodometric tests. The article presents the integration of SH equation’s for the implemented tests and describes the GA optimization procedure in detail. The numerical simulations carried out confirm that the algorithm can perform an excellent calibration. Moreover, by repeating the same calibration a thousand times, a large number of equally valid parameter combinations have been derived. The analysis of these combinations allowed for analyzing model sensitivity to parameters, and the correlations between these.

The source code written in Python will soon be available on Github. If you are interested in the code, you can contact me at francisco.mendez@unich.it.

All comments and observations are welcome!

  1. Wang Shun
    Wang Shun 4 years ago

    Nice work!!

  2. Francisco Mendez Author
    Francisco Mendez 4 years ago

    thank you !

  3. Francisco Mendez Author
    Francisco Mendez 3 years ago

    The article object of the post has been published and can be consulted at the following link

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