Transforming Energy through Computational Excellence. Exascale Computing: Combustion; Deep Learning for Presumed Probability Density Function (PDF) Models

Research output: NRELFact Sheet

Abstract

NREL researchers use advanced machine learning techniques to define improved methods using deep learning models to resolve reacting flows in turbulent combustion flows, reducing the computational burden, increasing computational speed, and improving accuracy. These advancements reduce cost and improve fidelity of rapid-turn-around engineering calculations.
Original languageAmerican English
StatePublished - 2021

NREL Publication Number

  • NREL/FS-2C00-80882

Keywords

  • combustion
  • deep learning
  • DNN
  • exascale computing
  • probability density function

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