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<p>We present a comprehensive dataset of two-phase flow Lattice-Boltzmann simulations, generated using over 100 million GPU hours, covering a wide range of wetting conditions, capillary numbers, and porous geometries. While multiphase flow has traditionally been studied through laboratory experiments, the growing power of computational simulations provides a scalable and efficient alternative. Our simulations, validated against synchrotron beamline experiments, reveal key insights into the effects of wettability, ganglion dynamics, and flow behaviors that can be used to either substantiate current upscaling theories or develop new approaches. The dataset includes 50 relative permeability curves and over 25,000 distinct fluid configurations. Acquiring equivalent data through experiments would be impractical using current techniques, and the computational resources required far exceed those typically available without direct access to high-performance facilities. This open-access dataset enables broad collaboration within the porous media research community and offers a valuable foundation for future studies on pore-scale transport, relative permeability prediction, and data-driven modeling approaches.</p>

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Lattice-Boltzmann for Porous Media: 100M+ GPU Hours

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月17日

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  • Ryan T. Armstrong,
  • Omid Tavakkoli,
  • Ying Da Wang,
  • Zhe Li,
  • Peyman Mostaghimi,
  • Steffen Berg,
  • Thomas Ramstad,
  • Maja Rücker,
  • James McClure

摘要

We present a comprehensive dataset of two-phase flow Lattice-Boltzmann simulations, generated using over 100 million GPU hours, covering a wide range of wetting conditions, capillary numbers, and porous geometries. While multiphase flow has traditionally been studied through laboratory experiments, the growing power of computational simulations provides a scalable and efficient alternative. Our simulations, validated against synchrotron beamline experiments, reveal key insights into the effects of wettability, ganglion dynamics, and flow behaviors that can be used to either substantiate current upscaling theories or develop new approaches. The dataset includes 50 relative permeability curves and over 25,000 distinct fluid configurations. Acquiring equivalent data through experiments would be impractical using current techniques, and the computational resources required far exceed those typically available without direct access to high-performance facilities. This open-access dataset enables broad collaboration within the porous media research community and offers a valuable foundation for future studies on pore-scale transport, relative permeability prediction, and data-driven modeling approaches.