Abstract
AbstractIn this contribution we present an approach to generate a data driven surrogate model for the prediction of permeabilities and flow through two dimensional random micro‐heterogeneous materials. The laminar flow is well described by Darcy's law. In order to achieve an efficient computational tool for the generation of the database (up to 103 realizations), needed for the training of the neural networks, we apply a stochastic model based on the Brownian motion. The stationary state of the resulting stochastic model solves the Darcy equation and can be iteratively solved by a Monte Carlo approach applied to a particle simulation. Improved numerical efficiency can be yield by usage of the related transition matrix.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
