As computational resources continue to evolve, NETL researchers look to new and more powerful tools to bolster their ability to model complex fossil energy power systems. The Lab has decades of experience developing this kind of software — known as computational fluid dynamics (CFD) code — including the award-winning Multiphase Flow with Interphase eXchanges (MFiX). In recent years, machine learning (ML) techniques have been integrated into powerful computational platforms like Google’s Tensor Flow, which is revolutionizing the way NETL researchers write CFD code to accelerate the design of more energy-efficient systems.
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