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Related Experiment Videos

Generation of long-range correlations in large systems as an optimization problem.

Hossein Hamzehpour1, Muhammad Sahimi

  • 1Institute for Advanced Studies in Basic Sciences, Gava Zang, Zanjan, Iran.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|June 29, 2006
PubMed
Summary

This study introduces an efficient optimization method using simulated annealing to generate long-range correlations in large systems, crucial for modeling porous media with limited data.

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Area of Science:

  • Geosciences
  • Computational Science
  • Materials Science

Background:

  • Large-scale porous media exhibit long-range correlations in properties like permeability and porosity.
  • Limited data availability poses challenges for accurate modeling and prediction of fluid flow.
  • Previous techniques often suffer from numerical limitations in generating these correlations.

Purpose of the Study:

  • To develop an efficient method for generating long-range correlations in large systems.
  • To construct an optimal model for large-scale porous media that honors existing data and correlation functions.
  • To accurately predict fluid flow behavior in porous media.

Main Methods:

  • Formulating the generation of long-range correlations as an optimization problem.

Related Experiment Videos

  • Utilizing simulated annealing to generate d-dimensional arrays with desired correlations.
  • Basing the optimization process on the data's correlation function.

    • Main Results:

    • The proposed method efficiently generates long-range correlations, honoring existing data.
    • The approach overcomes numerical difficulties associated with previous techniques.
    • The method is general, applicable to various correlation functions and media types (isotropic/anisotropic).

    Conclusions:

    • The simulated annealing-based optimization offers an efficient and accurate solution for modeling complex porous media.
    • This method provides a robust framework for handling limited data and predicting fluid flow.
    • The technique's generality makes it applicable to a wide range of scientific and engineering problems involving long-range correlations.