Physics-Informed Learning Machines for Multiscale and Multiphysics Problems

An image of various science-based visuals rolling out from a film reel labeled "philms."

(Image courtesy of Courtland Johnson | Pacific Northwest National Laboratory)

The PhILMs ("films") Center is a collaboration among Pacific Northwest National Laboratory and Sandia Laboratories, with academic partners at Brown University, Massachusetts Institute of Technology, Stanford University, and the University of California, Santa Barbara.

PhILMs is uncovering hidden physics based on new developments in deep learning, a computing technique that harnesses the power of machine learning and big data.

PhILMs investigators are developing physics-informed learning machines by encoding physics knowledge into deep learning networks to:

  • Design functional materials with tunable properties.
  • Solve longstanding problems in combustion, subsurface and earth systems, all exhibiting scaling cascades.
  • Establish probabilistic scientific computing as a new discipline at the interface of computational mathematics, multifidelity data, information fusion, and deep learning.

This work is supported by the Applied Mathematics Program within the U.S. Department of Energy Office of Advanced Scientific Computing Research.

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